def _query(self, query):
result = Data()
curr = self.db.execute(query)
result.meta.format = "table"
result.header = [d[0] for d in curr.description] if curr.description else None
result.data = curr.fetchall()
return result
def _send_email(self):
try:
if not self.accumulation:
return
with Closer(connect_to_region(
self.settings.region,
aws_access_key_id=unwrap(self.settings.aws_access_key_id),
aws_secret_access_key=unwrap(self.settings.aws_secret_access_key)
)) as conn:
# WHO ARE WE SENDING TO
emails = Data()
for template, params in self.accumulation:
content = expand_template(template, params)
emails[literal_field(self.settings.to_address)] += [content]
for c in self.cc:
if any(c in params.params.error for c in c.contains):
emails[literal_field(c.to_address)] += [content]
# SEND TO EACH
for to_address, content in emails.items():
conn.send_email(
source=self.settings.from_address,
to_addresses=listwrap(to_address),
subject=self.settings.subject,
body="\n\n".join(content),
format="text"
)
self.next_send = Date.now() + self.settings.max_interval
self.accumulation = []
except Exception as e:
self.next_send = Date.now() + self.settings.max_interval
Log.warning("Could not send", e)
def _send_email(self):
try:
if not self.accumulation:
return
with Emailer(self.settings) as emailer:
# WHO ARE WE SENDING TO
emails = Data()
for template, params in self.accumulation:
content = expand_template(template, params)
emails[literal_field(self.settings.to_address)] += [content]
for c in self.cc:
if any(d in params.params.error for d in c.contains):
emails[literal_field(c.to_address)] += [content]
# SEND TO EACH
for to_address, content in emails.items():
emailer.send_email(
from_address=self.settings.from_address,
to_address=listwrap(to_address),
subject=self.settings.subject,
text_data="\n\n".join(content)
)
self.accumulation = []
except Exception as e:
Log.warning("Could not send", e)
finally:
self.next_send = Date.now() + self.settings.average_interval * (2 * Random.float())
def list(self, prefix=None, marker=None, delimiter=None):
# https://s3.amazonaws.com/net-mozaws-stage-fx-test-activedata?marker=jenkins-go-bouncer.prod-3019/py27.log
# <ListBucketResult>
# <Name>net-mozaws-stage-fx-test-activedata</Name>
# <Prefix/>
# <Marker>jenkins-go-bouncer.prod-3019/py27.log</Marker>
# <MaxKeys>1000</MaxKeys>
# <IsTruncated>true</IsTruncated>
# <Contents>
# <Key>jenkins-go-bouncer.prod-3020/py27.log</Key>
# <LastModified>2017-03-05T07:02:20.000Z</LastModified>
# <ETag>"69dcb19e91eb3eec51e1b659801523d6"</ETag>
# <Size>10037</Size>
# <StorageClass>STANDARD</StorageClass>
state = Data()
state.prefix =prefix
state.delimiter = delimiter
state.marker = marker
state.get_more = True
def more():
xml = http.get(self.url + "?" + value2url_param(state)).content
data = BeautifulSoup(xml, 'xml')
state.get_more = data.find("istruncated").contents[0] == "true"
contents = data.findAll("contents")
state.marker = contents[-1].find("key").contents[0]
return [{k: t(d.find(k).contents[0]) for k, t in content_keys.items()} for d in contents]
while state.get_more:
content = more()
for c in content:
yield wrap(c)
def __init__(self, **kwargs):
Data.__init__(self)
self.count = 0
self.mean = None
self.variance = None
self.skew = None
self.kurtosis = None
if "samples" in kwargs:
s = ZeroMoment2Stats(ZeroMoment.new_instance(kwargs["samples"]))
self.count = s.count
self.mean = s.mean
self.variance = s.variance
self.skew = s.skew
self.kurtosis = s.kurtosis
return
if "count" not in kwargs:
self.count = 0
self.mean = None
self.variance = None
self.skew = None
self.kurtosis = None
elif "mean" not in kwargs:
self.count = kwargs["count"]
self.mean = None
self.variance = None
self.skew = None
self.kurtosis = None
elif "variance" not in kwargs and "std" not in kwargs:
self.count = kwargs["count"]
self.mean = kwargs["mean"]
self.variance = 0
self.skew = None
self.kurtosis = None
elif "skew" not in kwargs:
self.count = kwargs["count"]
self.mean = kwargs["mean"]
self.variance = kwargs["variance"] if "variance" in kwargs else kwargs["std"] ** 2
self.skew = None
self.kurtosis = None
elif "kurtosis" not in kwargs:
self.count = kwargs["count"]
self.mean = kwargs["mean"]
self.variance = kwargs["variance"] if "variance" in kwargs else kwargs["std"] ** 2
self.skew = kwargs["skew"]
self.kurtosis = None
else:
self.count = kwargs["count"]
self.mean = kwargs["mean"]
self.variance = kwargs["variance"] if "variance" in kwargs else kwargs["std"] ** 2
self.skew = kwargs["skew"]
self.kurtosis = kwargs["kurtosis"]
class StructuredLogger_usingThreadedStream(StructuredLogger):
# stream CAN BE AN OBJCET WITH write() METHOD, OR A STRING
# WHICH WILL eval() TO ONE
def __init__(self, stream):
assert stream
if isinstance(stream, text_type):
name = stream
stream = self.stream = eval(stream)
if name.startswith("sys.") and PY3:
self.stream = Data(write=lambda d: stream.write(d.decode('utf8')))
else:
name = "stream"
self.stream = stream
# WRITE TO STREAMS CAN BE *REALLY* SLOW, WE WILL USE A THREAD
from mo_threads import Queue
def utf8_appender(value):
if isinstance(value, text_type):
value = value.encode('utf8')
self.stream.write(value)
appender = utf8_appender
self.queue = Queue("queue for " + self.__class__.__name__ + "(" + name + ")", max=10000, silent=True)
self.thread = Thread("log to " + self.__class__.__name__ + "(" + name + ")", time_delta_pusher, appender=appender, queue=self.queue, interval=0.3)
self.thread.parent.remove_child(self.thread) # LOGGING WILL BE RESPONSIBLE FOR THREAD stop()
self.thread.start()
def write(self, template, params):
try:
self.queue.add({"template": template, "params": params})
return self
except Exception as e:
raise e # OH NO!
def stop(self):
try:
self.queue.add(THREAD_STOP) # BE PATIENT, LET REST OF MESSAGE BE SENT
self.thread.join()
except Exception as e:
if DEBUG_LOGGING:
raise e
try:
self.queue.close()
except Exception as f:
if DEBUG_LOGGING:
raise f
class FakeES():
@override
def __init__(self, filename, host="fake", index="fake", kwargs=None):
self.settings = kwargs
self.file = File(filename)
self.cluster= Null
try:
self.data = mo_json.json2value(self.file.read())
except Exception as e:
self.data = Data()
def search(self, query):
query = wrap(query)
f = jx.get(query.query.filtered.filter)
filtered = wrap([{"_id": i, "_source": d} for i, d in self.data.items() if f(d)])
if query.fields:
return wrap({"hits": {"total": len(filtered), "hits": [{"_id": d._id, "fields": unwrap(jx.select([unwrap(d._source)], query.fields)[0])} for d in filtered]}})
else:
return wrap({"hits": {"total": len(filtered), "hits": filtered}})
def extend(self, records):
"""
JUST SO WE MODEL A Queue
"""
records = {
v["id"]: v["value"] if "value" in v else mo_json.json2value(v['json'])
for v in records
}
unwrap(self.data).update(records)
self.refresh()
Log.note("{{num}} documents added", num=len(records))
def add(self, record):
if isinstance(record, list):
Log.error("no longer accepting lists, use extend()")
return self.extend([record])
def delete_record(self, filter):
f = esfilter2where(filter)
self.data = wrap({k: v for k, v in self.data.items() if not f(v)})
def refresh(self, *args, **kwargs):
data_as_json = mo_json.value2json(self.data, pretty=True)
self.file.write(data_as_json)
def set_refresh_interval(self, seconds):
pass
def url_param2value(param):
"""
CONVERT URL QUERY PARAMETERS INTO DICT
"""
if isinstance(param, unicode):
param = param.encode("ascii")
def _decode(v):
output = []
i = 0
while i < len(v):
c = v[i]
if c == "%":
d = (v[i + 1:i + 3]).decode("hex")
output.append(d)
i += 3
else:
output.append(c)
i += 1
output = (b"".join(output)).decode("latin1")
try:
if not _Log:
_late_import()
return _json2value(output)
except Exception:
pass
return output
query = Data()
for p in param.split(b'&'):
if not p:
continue
if p.find(b"=") == -1:
k = p
v = True
else:
k, v = p.split(b"=")
v = _decode(v)
u = query.get(k)
if u is None:
query[k] = v
elif isinstance(u, list):
u += [v]
else:
query[k] = [u, v]
return query
def _normalize_select_no_context(select, schema=None):
"""
SAME NORMALIZE, BUT NO SOURCE OF COLUMNS
"""
if not _Column:
_late_import()
if isinstance(select, text_type):
select = Data(value=select)
else:
select = wrap(select)
output = select.copy()
if not select.value:
output.name = coalesce(select.name, select.aggregate)
if output.name:
output.value = jx_expression(".", schema=schema)
else:
return Null
elif isinstance(select.value, text_type):
if select.value.endswith(".*"):
name = select.value[:-2]
output.name = coalesce(select.name, name)
output.value = LeavesOp("leaves", Variable(name), prefix=coalesce(select.prefix, name))
else:
if select.value == ".":
output.name = coalesce(select.name, select.aggregate, ".")
output.value = jx_expression(select.value, schema=schema)
elif select.value == "*":
output.name = coalesce(select.name, select.aggregate, ".")
output.value = LeavesOp("leaves", Variable("."))
else:
output.name = coalesce(select.name, select.value, select.aggregate)
output.value = jx_expression(select.value, schema=schema)
elif isinstance(select.value, (int, float)):
if not output.name:
output.name = text_type(select.value)
output.value = jx_expression(select.value, schema=schema)
else:
output.value = jx_expression(select.value, schema=schema)
if not output.name:
Log.error("expecting select to have a name: {{select}}", select= select)
if output.name.endswith(".*"):
Log.error("{{name|quote}} is invalid select", name=output.name)
output.aggregate = coalesce(canonical_aggregates[select.aggregate].name, select.aggregate, "none")
output.default = coalesce(select.default, canonical_aggregates[output.aggregate].default)
return output
def url_param2value(param):
"""
CONVERT URL QUERY PARAMETERS INTO DICT
"""
if param == None:
return Null
if param == None:
return Null
def _decode(v):
output = []
i = 0
while i < len(v):
c = v[i]
if c == "%":
d = hex2chr(v[i + 1:i + 3])
output.append(d)
i += 3
else:
output.append(c)
i += 1
output = text_type("".join(output))
try:
return json2value(output)
except Exception:
pass
return output
query = Data()
for p in param.split('&'):
if not p:
continue
if p.find("=") == -1:
k = p
v = True
else:
k, v = p.split("=")
v = _decode(v)
u = query.get(k)
if u is None:
query[k] = v
elif is_list(u):
u += [v]
else:
query[k] = [u, v]
return query
def __init__(self, filename, host="fake", index="fake", kwargs=None):
self.settings = kwargs
self.filename = kwargs.filename
try:
self.data = mo_json.json2value(File(self.filename).read())
except Exception:
self.data = Data()
def __init__(self, stream):
assert stream
if isinstance(stream, text_type):
name = stream
stream = self.stream = eval(stream)
if name.startswith("sys.") and PY3:
self.stream = Data(write=lambda d: stream.write(d.decode('utf8')))
else:
name = "stream"
self.stream = stream
# WRITE TO STREAMS CAN BE *REALLY* SLOW, WE WILL USE A THREAD
from mo_threads import Queue
def utf8_appender(value):
if isinstance(value, text_type):
value = value.encode('utf8')
self.stream.write(value)
appender = utf8_appender
self.queue = Queue("queue for " + self.__class__.__name__ + "(" + name + ")", max=10000, silent=True)
self.thread = Thread("log to " + self.__class__.__name__ + "(" + name + ")", time_delta_pusher, appender=appender, queue=self.queue, interval=0.3)
self.thread.parent.remove_child(self.thread) # LOGGING WILL BE RESPONSIBLE FOR THREAD stop()
self.thread.start()
def __init__(self, filename, host="fake", index="fake", kwargs=None):
self.settings = kwargs
self.file = File(filename)
self.cluster= Null
try:
self.data = mo_json.json2value(self.file.read())
except Exception as e:
self.data = Data()
def encrypt(text, _key, salt=None):
"""
RETURN JSON OF ENCRYPTED DATA {"salt":s, "length":l, "data":d}
"""
if not isinstance(text, unicode):
Log.error("only unicode is encrypted")
if _key is None:
Log.error("Expecting a key")
if isinstance(_key, str):
_key = bytearray(_key)
if salt is None:
salt = Random.bytes(16)
data = bytearray(text.encode("utf8"))
# Initialize encryption using key and iv
key_expander_256 = key_expander.KeyExpander(256)
expanded_key = key_expander_256.expand(_key)
aes_cipher_256 = aes_cipher.AESCipher(expanded_key)
aes_cbc_256 = cbc_mode.CBCMode(aes_cipher_256, 16)
aes_cbc_256.set_iv(salt)
output = Data()
output.type = "AES256"
output.salt = bytes2base64(salt)
output.length = len(data)
encrypted = bytearray()
for _, d in _groupby16(data):
encrypted.extend(aes_cbc_256.encrypt_block(d))
output.data = bytes2base64(encrypted)
json = get_module("mo_json").value2json(output)
if DEBUG:
test = decrypt(json, _key)
if test != text:
Log.error("problem with encryption")
return json
def encrypt(text, _key, salt=None):
"""
RETURN {"salt":s, "length":l, "data":d} -> JSON -> UTF8
"""
if is_text(text):
encoding = 'utf8'
data = bytearray(text.encode("utf8"))
elif is_binary(text):
encoding = None
if PY2:
data = bytearray(text)
else:
data = text
if _key is None:
Log.error("Expecting a key")
if is_binary(_key):
_key = bytearray(_key)
if salt is None:
salt = Random.bytes(16)
# Initialize encryption using key and iv
key_expander_256 = key_expander.KeyExpander(256)
expanded_key = key_expander_256.expand(_key)
aes_cipher_256 = aes_cipher.AESCipher(expanded_key)
aes_cbc_256 = cbc_mode.CBCMode(aes_cipher_256, 16)
aes_cbc_256.set_iv(salt)
output = Data()
output.type = "AES256"
output.salt = bytes2base64(salt)
output.length = len(data)
output.encoding = encoding
encrypted = bytearray()
for _, d in _groupby16(data):
encrypted.extend(aes_cbc_256.encrypt_block(d))
output.data = bytes2base64(encrypted)
json = get_module("mo_json").value2json(output, pretty=True).encode('utf8')
if DEBUG:
test = decrypt(json, _key)
if test != text:
Log.error("problem with encryption")
return json
def __init__(self, _file):
"""
file - USES FILE FOR PERSISTENCE
"""
self.file = File.new_instance(_file)
self.lock = Lock("lock for persistent queue using file " + self.file.name)
self.please_stop = Signal()
self.db = Data()
self.pending = []
if self.file.exists:
for line in self.file:
with suppress_exception:
delta = mo_json.json2value(line)
apply_delta(self.db, delta)
if self.db.status.start == None: # HAPPENS WHEN ONLY ADDED TO QUEUE, THEN CRASH
self.db.status.start = 0
self.start = self.db.status.start
# SCRUB LOST VALUES
lost = 0
for k in self.db.keys():
with suppress_exception:
if k!="status" and int(k) < self.start:
self.db[k] = None
lost += 1
# HAPPENS FOR self.db.status, BUT MAYBE OTHER PROPERTIES TOO
if lost:
Log.warning("queue file had {{num}} items lost", num= lost)
DEBUG and Log.note("Persistent queue {{name}} found with {{num}} items", name=self.file.abspath, num=len(self))
else:
self.db.status = Data(
start=0,
end=0
)
self.start = self.db.status.start
DEBUG and Log.note("New persistent queue {{name}}", name=self.file.abspath)
def get_more(please_stop):
more.append(
es09.util.post(es, Data(filter=more_filter,
fields=es_query.fields), query.limit))
class FakeES():
@override
def __init__(self, filename, host="fake", index="fake", kwargs=None):
self.settings = kwargs
self.filename = filename
try:
self.data = mo_json.json2value(File(self.filename).read())
except Exception as e:
self.data = Data()
def search(self, query):
query = wrap(query)
f = jx.get(query.query.filtered.filter)
filtered = wrap([{
"_id": i,
"_source": d
} for i, d in self.data.items() if f(d)])
if query.fields:
return wrap({
"hits": {
"total":
len(filtered),
"hits": [{
"_id":
d._id,
"fields":
unwrap(
jx.select([unwrap(d._source)], query.fields)[0])
} for d in filtered]
}
})
else:
return wrap({"hits": {"total": len(filtered), "hits": filtered}})
def extend(self, records):
"""
JUST SO WE MODEL A Queue
"""
records = {
v["id"]:
v["value"] if "value" in v else mo_json.json2value(v['json'])
for v in records
}
unwrap(self.data).update(records)
data_as_json = mo_json.value2json(self.data, pretty=True)
File(self.filename).write(data_as_json)
Log.note("{{num}} documents added", num=len(records))
def add(self, record):
if isinstance(record, list):
Log.error("no longer accepting lists, use extend()")
return self.extend([record])
def delete_record(self, filter):
f = convert.esfilter2where(filter)
self.data = wrap({k: v for k, v in self.data.items() if not f(v)})
def set_refresh_interval(self, seconds):
pass
def _convert_range(self, range):
if range == None:
return None
return Data(min=range.min, max=range.max)
def __init__(
self,
host,
index, # THE NAME OF THE SNOWFLAKE (IF WRITING)
alias=None, # THE NAME OF THE SNOWFLAKE (FOR READING)
type=None,
name=None, # THE FULL NAME OF THE TABLE (THE NESTED PATH INTO THE SNOWFLAKE)
port=9200,
read_only=True,
timeout=None, # NUMBER OF SECONDS TO WAIT FOR RESPONSE, OR SECONDS TO WAIT FOR DOWNLOAD (PASSED TO requests)
wait_for_active_shards=1, # ES WRITE CONSISTENCY (https://www.elastic.co/guide/en/elasticsearch/reference/1.7/docs-index_.html#index-consistency)
typed=None,
kwargs=None):
Container.__init__(self)
if not container.config.default:
container.config.default = {
"type": "elasticsearch",
"settings": unwrap(kwargs)
}
self.edges = Data() # SET EARLY, SO OTHER PROCESSES CAN REQUEST IT
self.worker = None
self.settings = kwargs
self._namespace = ElasticsearchMetadata(kwargs=kwargs)
self.name = name = self._namespace._find_alias(
coalesce(alias, index, name))
if read_only:
self.es = elasticsearch.Alias(alias=name,
index=None,
kwargs=kwargs)
else:
self.es = elasticsearch.Cluster(kwargs=kwargs).get_index(
read_only=read_only, kwargs=kwargs)
self._ensure_max_result_window_set(name)
self.settings.type = self.es.settings.type
self.stats = QueryStats(self.es.cluster)
columns = self.snowflake.columns # ABSOLUTE COLUMNS
is_typed = any(c.es_column == EXISTS_TYPE for c in columns)
if typed == None:
# SWITCH ON TYPED MODE
self.typed = is_typed
else:
if is_typed != typed:
Log.error(
"Expecting given typed {{typed}} to match {{is_typed}}",
typed=typed,
is_typed=is_typed)
self.typed = typed
if not typed:
# ADD EXISTENCE COLUMNS
all_paths = {'.': None} # MAP FROM path TO parent TO MAKE A TREE
def nested_path_of(v):
if v == '.':
return ('.', )
return (v, ) + nested_path_of(all_paths[v])
query_paths = sort_using_key(set(
step for path in self.snowflake.query_paths for step in path),
key=lambda p: len(split_field(p)))
for step in query_paths:
if step in all_paths:
continue
else:
best = '.'
for candidate in all_paths.keys():
if startswith_field(step, candidate):
if startswith_field(candidate, best):
best = candidate
all_paths[step] = best
for p in all_paths.keys():
nested_path = nested_path_of(p)
try:
self.namespace.meta.columns.add(
Column(name=p,
es_column=p,
es_index=self.name,
es_type=OBJECT,
jx_type=OBJECT,
nested_path=nested_path,
multi=1001 if last(split_field(p))
== NESTED_TYPE else None,
last_updated=Date.now()))
except Exception as e:
raise e
from mo_json import json2value, value2json
from mo_kwargs import override
from mo_logs import Log
from mo_logs.exceptions import Except
from mo_threads import Lock, Till
from mo_times import Timer, Duration
from requests import Response, sessions
from mo_http.big_data import ibytes2ilines, icompressed2ibytes, safe_size, ibytes2icompressed, bytes2zip, zip2bytes
DEBUG = False
FILE_SIZE_LIMIT = 100 * 1024 * 1024
MIN_READ_SIZE = 8 * 1024
ZIP_REQUEST = False
default_headers = Data(
) # TODO: MAKE THIS VARIABLE A SPECIAL TYPE OF EXPECTED MODULE PARAMETER SO IT COMPLAINS IF NOT SET
default_timeout = 600
DEFAULTS = {
"allow_redirects": True,
"stream": True,
"verify": True,
"timeout": 600,
"zip": False,
"retry": {
"times": 1,
"sleep": 0,
"http": False
}
}
_warning_sent = False
request_count = 0
def select(self, fields):
if is_data(fields):
fields = fields.value
if is_text(fields):
# RETURN LIST OF VALUES
if len(split_field(fields)) == 1:
if self.path[0] == fields:
return [d[1] for d in self.data]
else:
return [d[0][fields] for d in self.data]
else:
keys = split_field(fields)
depth = coalesce(
MIN([
i for i, (k, p) in enumerate(zip(keys, self.path))
if k != p
]), len(self.path)) # LENGTH OF COMMON PREFIX
short_key = keys[depth:]
output = FlatList()
_select1((wrap(d[depth]) for d in self.data), short_key, 0,
output)
return output
if is_list(fields):
output = FlatList()
meta = []
for f in fields:
if hasattr(f.value, "__call__"):
meta.append((f.name, f.value))
else:
meta.append(
(f.name, functools.partial(lambda v, d: d[v],
f.value)))
for row in self._values():
agg = Data()
for name, f in meta:
agg[name] = f(row)
output.append(agg)
return output
# meta = []
# for f in fields:
# keys = split_field(f.value)
# depth = coalesce(MIN([i for i, (k, p) in enumerate(zip(keys, self.path)) if k != p]), len(self.path)) # LENGTH OF COMMON PREFIX
# short_key = join_field(keys[depth:])
#
# meta.append((f.name, depth, short_key))
#
# for row in self._data:
# agg = Data()
# for name, depth, short_key in meta:
# if short_key:
# agg[name] = row[depth][short_key]
# else:
# agg[name] = row[depth]
# output.append(agg)
# return output
Log.error("multiselect over FlatList not supported")
def format_table(aggs, es_query, query, decoders, all_selects):
new_edges = wrap(count_dim(aggs, es_query, decoders))
dims = tuple(len(e.domain.partitions) + (0 if e.allowNulls is False else 1) for e in new_edges)
rank = len(dims)
header = tuple(new_edges.name + all_selects.name)
name2index = {s.name: i + rank for i, s in enumerate(all_selects)}
def data():
is_sent = Matrix(dims=dims)
give_me_zeros = query.sort and not query.groupby
if give_me_zeros:
# WE REQUIRE THE ZEROS FOR SORTING
all_coord = is_sent._all_combos() # TRACK THE EXPECTED COMBINATIONS
ordered_coord = all_coord.next()[::-1]
output = None
for row, coord, agg, ss in aggs_iterator(aggs, es_query, decoders):
if coord != ordered_coord:
# output HAS BEEN YIELDED, BUT SET THE DEFAULT VALUES
if output is not None:
for s in all_selects:
i = name2index[s.name]
if output[i] is None:
output[i] = s.default
# WE CAN GET THE SAME coord MANY TIMES, SO ONLY ADVANCE WHEN NOT
ordered_coord = all_coord.next()[::-1]
while coord != ordered_coord:
# HAPPENS WHEN THE coord IS AHEAD OF ordered_coord
record = [d.get_value(ordered_coord[i]) for i, d in enumerate(decoders)] + [s.default for s in all_selects]
yield record
ordered_coord = all_coord.next()[::-1]
# coord == missing_coord
output = [d.get_value(c) for c, d in zip(coord, decoders)] + [None for s in all_selects]
for select in ss:
v = select.pull(agg)
if v != None:
union(output, name2index[select.name], v, select.aggregate)
yield output
else:
last_coord = None # HANG ONTO THE output FOR A BIT WHILE WE FILL THE ELEMENTS
output = None
for row, coord, agg, ss in aggs_iterator(aggs, es_query, decoders):
if coord != last_coord:
if output:
# SET DEFAULTS
for i, s in enumerate(all_selects):
v = output[rank+i]
if v == None:
output[rank+i] = s.default
yield output
output = is_sent[coord]
if output == None:
output = is_sent[coord] = [d.get_value(c) for c, d in zip(coord, decoders)] + [None for _ in all_selects]
last_coord = coord
# THIS IS A TRICK! WE WILL UPDATE A ROW THAT WAS ALREADY YIELDED
for select in ss:
v = select.pull(agg)
if v != None:
union(output, name2index[select.name], v, select.aggregate)
if output:
# SET DEFAULTS ON LAST ROW
for i, s in enumerate(all_selects):
v = output[rank+i]
if v == None:
output[rank+i] = s.default
yield output
# EMIT THE MISSING CELLS IN THE CUBE
if not query.groupby:
for coord, output in is_sent:
if output == None:
record = [d.get_value(c) for c, d in zip(coord, decoders)] + [s.default for s in all_selects]
yield record
return Data(
meta={"format": "table"},
header=header,
data=list(data())
)
def _update_cardinality(self, column):
"""
QUERY ES TO FIND CARDINALITY AND PARTITIONS FOR A SIMPLE COLUMN
"""
now = Date.now()
if column.es_index in self.index_does_not_exist:
return
if column.jx_type in STRUCT:
Log.error("not supported")
try:
if column.es_index == "meta.columns":
partitions = jx.sort([
g[column.es_column]
for g, _ in jx.groupby(self.meta.columns, column.es_column)
if g[column.es_column] != None
])
self.meta.columns.update({
"set": {
"partitions": partitions,
"count": len(self.meta.columns),
"cardinality": len(partitions),
"multi": 1,
"last_updated": now
},
"where": {
"eq": {
"es_index": column.es_index,
"es_column": column.es_column
}
}
})
return
if column.es_index == "meta.tables":
partitions = jx.sort([
g[column.es_column]
for g, _ in jx.groupby(self.meta.tables, column.es_column)
if g[column.es_column] != None
])
self.meta.columns.update({
"set": {
"partitions": partitions,
"count": len(self.meta.tables),
"cardinality": len(partitions),
"multi": 1,
"last_updated": now
},
"where": {
"eq": {
"es_index": column.es_index,
"es_column": column.es_column
}
}
})
return
es_index = column.es_index.split(".")[0]
is_text = [
cc for cc in self.meta.columns
if cc.es_column == column.es_column and cc.es_type == "text"
]
if is_text:
# text IS A MULTIVALUE STRING THAT CAN ONLY BE FILTERED
result = self.es_cluster.post("/" + es_index + "/_search",
data={
"aggs": {
"count": {
"filter": {
"match_all": {}
}
}
},
"size": 0
})
count = result.hits.total
cardinality = max(1001, count)
multi = 1001
elif column.es_column == "_id":
result = self.es_cluster.post("/" + es_index + "/_search",
data={
"query": {
"match_all": {}
},
"size": 0
})
count = cardinality = result.hits.total
multi = 1
elif column.es_type == BOOLEAN:
result = self.es_cluster.post("/" + es_index + "/_search",
data={
"aggs": {
"count":
_counting_query(column)
},
"size": 0
})
count = result.hits.total
cardinality = 2
DEBUG and Log.note("{{table}}.{{field}} has {{num}} parts",
table=column.es_index,
field=column.es_column,
num=cardinality)
self.meta.columns.update({
"set": {
"count": count,
"cardinality": cardinality,
"partitions": [False, True],
"multi": 1,
"last_updated": now
},
"clear": ["partitions"],
"where": {
"eq": {
"es_index": column.es_index,
"es_column": column.es_column
}
}
})
return
else:
es_query = {
"aggs": {
"count": _counting_query(column),
"_filter": {
"aggs": {
"multi": {
"max": {
"script":
"doc[" + quote(column.es_column) +
"].values.size()"
}
}
},
"filter": {
"bool": {
"should": [{
"range": {
"etl.timestamp.~n~": {
"gte": (Date.today() - WEEK)
}
}
}, {
"bool": {
"must_not": {
"exists": {
"field":
"etl.timestamp.~n~"
}
}
}
}]
}
}
}
},
"size": 0
}
result = self.es_cluster.post("/" + es_index + "/_search",
data=es_query)
agg_results = result.aggregations
count = result.hits.total
cardinality = coalesce(agg_results.count.value,
agg_results.count._nested.value,
agg_results.count.doc_count)
multi = int(coalesce(agg_results._filter.multi.value, 1))
if cardinality == None:
Log.error("logic error")
query = Data(size=0)
if column.es_column == "_id":
self.meta.columns.update({
"set": {
"count": cardinality,
"cardinality": cardinality,
"multi": 1,
"last_updated": now
},
"clear": ["partitions"],
"where": {
"eq": {
"es_index": column.es_index,
"es_column": column.es_column
}
}
})
return
elif cardinality > 1000 or (count >= 30 and cardinality == count
) or (count >= 1000
and cardinality / count > 0.99):
DEBUG and Log.note("{{table}}.{{field}} has {{num}} parts",
table=column.es_index,
field=column.es_column,
num=cardinality)
self.meta.columns.update({
"set": {
"count": count,
"cardinality": cardinality,
"multi": multi,
"last_updated": now
},
"clear": ["partitions"],
"where": {
"eq": {
"es_index": column.es_index,
"es_column": column.es_column
}
}
})
return
elif column.es_type in elasticsearch.ES_NUMERIC_TYPES and cardinality > 30:
DEBUG and Log.note("{{table}}.{{field}} has {{num}} parts",
table=column.es_index,
field=column.es_column,
num=cardinality)
self.meta.columns.update({
"set": {
"count": count,
"cardinality": cardinality,
"multi": multi,
"last_updated": now
},
"clear": ["partitions"],
"where": {
"eq": {
"es_index": column.es_index,
"es_column": column.es_column
}
}
})
return
elif len(column.nested_path) != 1:
query.aggs["_"] = {
"nested": {
"path": column.nested_path[0]
},
"aggs": {
"_nested": {
"terms": {
"field": column.es_column
}
}
}
}
elif cardinality == 0: # WHEN DOES THIS HAPPEN?
query.aggs["_"] = {"terms": {"field": column.es_column}}
else:
query.aggs["_"] = {
"terms": {
"field": column.es_column,
"size": cardinality
}
}
result = self.es_cluster.post("/" + es_index + "/_search",
data=query)
aggs = result.aggregations._
if aggs._nested:
parts = jx.sort(aggs._nested.buckets.key)
else:
parts = jx.sort(aggs.buckets.key)
DEBUG and Log.note(
"update metadata for {{column.es_index}}.{{column.es_column}} (id={{id}}) at {{time}}",
id=id(column),
column=column,
time=now)
self.meta.columns.update({
"set": {
"count": count,
"cardinality": cardinality,
"multi": multi,
"partitions": parts,
"last_updated": now
},
"where": {
"eq": {
"es_index": column.es_index,
"es_column": column.es_column
}
}
})
except Exception as e:
# CAN NOT IMPORT: THE TEST MODULES SETS UP LOGGING
# from tests.test_jx import TEST_TABLE
e = Except.wrap(e)
TEST_TABLE = "testdata"
is_missing_index = any(
w in e for w in
["IndexMissingException", "index_not_found_exception"])
is_test_table = column.es_index.startswith(
(TEST_TABLE_PREFIX, TEST_TABLE))
if is_missing_index:
# WE EXPECT TEST TABLES TO DISAPPEAR
Log.warning("Missing index {{col.es_index}}",
col=column,
cause=e)
self.meta.columns.update({
"clear": ".",
"where": {
"eq": {
"es_index": column.es_index
}
}
})
self.index_does_not_exist.add(column.es_index)
elif "No field found for" in e:
self.meta.columns.update({
"clear": ".",
"where": {
"eq": {
"es_index": column.es_index,
"es_column": column.es_column
}
}
})
Log.warning(
"Could not get column {{col.es_index}}.{{col.es_column}} info",
col=column,
cause=e)
else:
self.meta.columns.update({
"set": {
"last_updated": now
},
"clear": [
"count",
"cardinality",
"multi",
"partitions",
],
"where": {
"eq": {
"es_index": column.es_index,
"es_column": column.es_column
}
}
})
Log.warning(
"Could not get {{col.es_index}}.{{col.es_column}} info",
col=column,
cause=e)
def follow_paths(position, path, nested_path, done_relations,
no_nested_docs):
if position.name in self.settings.exclude:
return
if self.path_not_allowed(path):
return
if DEBUG:
Log.note("Trace {{path}}", path=path)
if position.name != "__ids__":
# USED TO CONFIRM WE CAN ACCESS THE TABLE (WILL THROW ERROR WHEN IF IT FAILS)
self.db.query(
ConcatSQL(
SQL_SELECT,
SQL_STAR,
SQL_FROM,
quote_column(position.schema, position.name),
SQL_LIMIT,
SQL_ONE,
))
if position.name in reference_all_tables:
no_nested_docs = True
if position.name in reference_only_tables:
return
curr_join_list = copy(nested_path_to_join[nested_path[0]])
###############################################################################
# INNER OBJECTS
###############################################################################
referenced_tables = list(
sort_using_key(
jx.groupby(
jx.filter(
relations,
{
"eq": {
"table.name": position.name,
"table.schema": position.schema,
}
},
),
"constraint.name",
),
key=lambda p: first(p[1]).column.name,
))
for g, constraint_columns in referenced_tables:
g = unwrap(g)
constraint_columns = deepcopy(constraint_columns)
if g["constraint.name"] in done_relations:
continue
if any(cc for cc in constraint_columns
if cc.referenced.table.name in self.settings.exclude):
continue
done_relations.add(g["constraint.name"])
many_to_one_joins = nested_path_to_join[nested_path[0]]
index = len(many_to_one_joins)
alias = "t" + text(index)
for c in constraint_columns:
c.referenced.table.alias = alias
c.table = position
many_to_one_joins.append({
"join_columns": constraint_columns,
"path": path,
"nested_path": nested_path,
})
# HANDLE THE COMMON *id SUFFIX
name = []
for cname, tname in zip(
constraint_columns.column.name,
constraint_columns.referenced.table.name,
):
if cname.startswith(tname):
name.append(tname)
elif cname.endswith("_id"):
name.append(cname[:-3])
else:
name.append(cname)
relation_string = many_to_one_string(constraint_columns[0])
step = "/".join(name)
if len(constraint_columns) == 1:
step = self.name_relations.get(relation_string, step)
referenced_column_path = concat_field(path, step)
if self.path_not_allowed(referenced_column_path):
continue
if referenced_column_path in reference_only_tables:
continue
col_pointer_name = relative_field(referenced_column_path,
nested_path[0])
for col in columns:
if (col.table.name
== constraint_columns[0].referenced.table.name
and col.table.schema
== constraint_columns[0].referenced.table.schema):
col_full_name = concat_field(
col_pointer_name, literal_field(col.column.name))
if (col.is_id and col.table.name == fact_table.name
and col.table.schema == fact_table.schema):
# ALWAYS SHOW THE ID OF THE FACT
c_index = len(output_columns)
output_columns.append({
"table_alias":
alias,
"column_alias":
"c" + text(c_index),
"column":
col,
"sort":
True,
"path":
referenced_column_path,
"nested_path":
nested_path,
"put":
col_full_name,
})
elif col.column.name == constraint_columns[
0].column.name:
c_index = len(output_columns)
output_columns.append({
"table_alias":
alias,
"column_alias":
"c" + text(c_index),
"column":
col,
"sort":
False,
"path":
referenced_column_path,
"nested_path":
nested_path,
"put":
col_full_name
if self.settings.show_foreign_keys else None,
})
elif col.is_id:
c_index = len(output_columns)
output_columns.append({
"table_alias":
alias,
"column_alias":
"c" + text(c_index),
"column":
col,
"sort":
False,
"path":
referenced_column_path,
"nested_path":
nested_path,
"put":
col_full_name
if self.settings.show_foreign_keys else None,
})
elif col.reference:
c_index = len(output_columns)
output_columns.append({
"table_alias":
alias,
"column_alias":
"c" + text(c_index),
"column":
col,
"sort":
False,
"path":
referenced_column_path,
"nested_path":
nested_path,
"put":
col_pointer_name
if not self.settings.show_foreign_keys else
col_full_name, # REFERENCE FIELDS CAN REPLACE THE WHOLE OBJECT BEING REFERENCED
})
elif col.include:
c_index = len(output_columns)
output_columns.append({
"table_alias":
alias,
"column_alias":
"c" + text(c_index),
"column":
col,
"sort":
False,
"path":
referenced_column_path,
"nested_path":
nested_path,
"put":
col_full_name,
})
if position.name in reference_only_tables:
continue
todo.append(
Data(
position=copy(constraint_columns[0].referenced.table),
path=referenced_column_path,
nested_path=nested_path,
done_relations=copy(done_relations),
no_nested_docs=no_nested_docs,
))
###############################################################################
# NESTED OBJECTS
###############################################################################
if not no_nested_docs:
nesting_tables = list(
sort_using_key(
jx.groupby(
jx.filter(
relations,
{
"eq": {
"referenced.table.name": position.name,
"referenced.table.schema":
position.schema,
}
},
),
"constraint.name",
),
key=lambda p: [(r.table.name, r.column.name)
for r in [first(p[1])]][0],
))
for g, constraint_columns in nesting_tables:
g = unwrap(g)
constraint_columns = deepcopy(constraint_columns)
if g["constraint.name"] in done_relations:
continue
done_relations.add(g["constraint.name"])
many_table = set(constraint_columns.table.name)
if not (many_table - self.settings.exclude):
continue
relation_string = one_to_many_string(constraint_columns[0])
step = "/".join(many_table)
if len(constraint_columns) == 1:
step = self.name_relations.get(relation_string, step)
referenced_column_path = concat_field(path, step)
if self.path_not_allowed(referenced_column_path):
continue
new_nested_path = [referenced_column_path] + nested_path
all_nested_paths.append(new_nested_path)
if referenced_column_path in nested_path_to_join:
Log.error(
"{{path}} already exists, try adding entry to name_relations",
path=referenced_column_path,
)
one_to_many_joins = nested_path_to_join[
referenced_column_path] = copy(curr_join_list)
index = len(one_to_many_joins)
alias = "t" + text(index)
for c in constraint_columns:
c.table.alias = alias
c.referenced.table = position
one_to_many_joins.append(
set_default(
{},
g,
{
"children": True,
"join_columns": constraint_columns,
"path": path,
"nested_path": nested_path,
},
))
for col in columns:
if (col.table.name == constraint_columns[0].table.name
and col.table.schema
== constraint_columns[0].table.schema):
col_full_name = join_field(
split_field(referenced_column_path)
[len(split_field(new_nested_path[0])):] +
[literal_field(col.column.name)])
if col.column.name == constraint_columns[
0].column.name:
c_index = len(output_columns)
output_columns.append({
"table_alias":
alias,
"column_alias":
"c" + text(c_index),
"column":
col,
"sort":
col.is_id,
"path":
referenced_column_path,
"nested_path":
new_nested_path,
"put":
col_full_name if
self.settings.show_foreign_keys else None,
})
elif col.is_id:
c_index = len(output_columns)
output_columns.append({
"table_alias":
alias,
"column_alias":
"c" + text(c_index),
"column":
col,
"sort":
col.is_id,
"path":
referenced_column_path,
"nested_path":
new_nested_path,
"put":
col_full_name if
self.settings.show_foreign_keys else None,
})
else:
c_index = len(output_columns)
output_columns.append({
"table_alias":
alias,
"column_alias":
"c" + text(c_index),
"column":
col,
"sort":
col.is_id,
"path":
referenced_column_path,
"nested_path":
new_nested_path,
"put":
col_full_name if col.include else None,
})
todo.append(
Data(
position=constraint_columns[0].table,
path=referenced_column_path,
nested_path=new_nested_path,
done_relations=copy(done_relations),
no_nested_docs=no_nested_docs,
))
def construct_docs(self, cursor, append, please_stop):
"""
:param cursor: ITERATOR OF RECORD TUPLES
:param append: METHOD TO CALL WITH CONSTRUCTED DOCUMENT
:return: (count, first, next, next_key)
number of documents added
the first document in the batch
the first document of the next batch
"""
null_values = set(self.settings.null_values) | {None}
doc_count = 0
columns = tuple(wrap(c) for c in self.columns)
with Timer("Downloading from MySQL"):
curr_doc = Null
row_count = 0
for row in cursor:
row_count += 1
if please_stop:
Log.error("Got `please_stop` signal")
nested_path = []
next_object = Data()
for c, value in zip(columns, row):
# columns ARE IN ORDER, FROM FACT ['.'] TO EVER-DEEPER-NESTED
if value in null_values:
# EVERY COLUMN THAT'S NOT NEEDED IS None
continue
if len(nested_path) < len(c.nested_path):
# EACH COLUMN IS DEEPER THAN THE NEXT
# THESE WILL BE THE id COLUMNS, WHICH ARE ALWAYS INCLUDED AND BEFORE ALL OTHER VALUES
nested_path = unwrap(c.nested_path)
next_object = Data()
next_object[c.put] = value
# OBJECT HAS BEEN CONSTRUCTED, LET'S PLACE IT WHERE IT BELONGS
if len(nested_path) > 1:
children = [curr_doc]
steps = list(reversed(nested_path))
parent_path = steps[0]
for path in steps[1:]:
parent = children[-1]
relative_path = relative_field(path, parent_path)
children = unwrap(parent[relative_path])
if not children:
children = parent[relative_path] = []
parent_path = path
children.append(next_object)
continue
# THE TOP-LEVEL next_object HAS BEEN ENCOUNTERED, EMIT THE PREVIOUS, AND COMPLETED curr_doc
if curr_doc == next_object:
Log.error(
"Expecting records. Did you select the wrong schema, or select records that do not exist?"
)
if curr_doc:
append(curr_doc["id"])
doc_count += 1
curr_doc = next_object
# DEAL WITH LAST RECORD
if curr_doc:
append(curr_doc["id"])
doc_count += 1
Log.note(
"{{doc_count}} documents ({{row_count}} db records)",
doc_count=doc_count,
row_count=row_count,
)
def _scan_database(self):
# GET ALL RELATIONS
raw_relations = self.db.query(
"""
SELECT
table_schema,
table_name,
referenced_table_schema,
referenced_table_name,
referenced_column_name,
constraint_name,
column_name,
ordinal_position
FROM
information_schema.key_column_usage
WHERE
referenced_column_name IS NOT NULL
""",
param=self.settings.database,
)
if not raw_relations:
Log.error("No relations in the database")
for r in self.settings.add_relations:
try:
lhs, rhs = map(strings.trim, r.split("->"))
lhs = lhs.split(".")
if len(lhs) == 2:
lhs = [self.settings.database.schema] + lhs
rhs = rhs.split(".")
if len(rhs) == 2:
rhs = [self.settings.database.schema] + rhs
to_add = Data(
ordinal_position=1, # CAN ONLY HANDLE 1-COLUMN RELATIONS
table_schema=lhs[0],
table_name=lhs[1],
column_name=lhs[2],
referenced_table_schema=rhs[0],
referenced_table_name=rhs[1],
referenced_column_name=rhs[2],
)
# CHECK IF EXISTING
if jx.filter(raw_relations, {"eq": to_add}):
Log.note("Relation {{relation}} already exists",
relation=r)
continue
to_add.constraint_name = Random.hex(20)
raw_relations.append(to_add)
except Exception as e:
Log.error("Could not parse {{line|quote}}", line=r, cause=e)
relations = jx.select(
raw_relations,
[
{
"name": "constraint.name",
"value": "constraint_name"
},
{
"name": "table.schema",
"value": "table_schema"
},
{
"name": "table.name",
"value": "table_name"
},
{
"name": "column.name",
"value": "column_name"
},
{
"name": "referenced.table.schema",
"value": "referenced_table_schema"
},
{
"name": "referenced.table.name",
"value": "referenced_table_name"
},
{
"name": "referenced.column.name",
"value": "referenced_column_name"
},
{
"name": "ordinal_position",
"value": "ordinal_position"
},
],
)
# GET ALL TABLES
raw_tables = self.db.query("""
SELECT
t.table_schema,
t.table_name,
c.constraint_name,
c.constraint_type,
k.column_name,
k.ordinal_position
FROM
information_schema.tables t
LEFT JOIN
information_schema.table_constraints c on c.table_name=t.table_name AND c.table_schema=t.table_schema and (constraint_type='UNIQUE' or constraint_type='PRIMARY KEY')
LEFT JOIN
information_schema.key_column_usage k on k.constraint_name=c.constraint_name AND k.table_name=t.table_name and k.table_schema=t.table_schema
ORDER BY
t.table_schema,
t.table_name,
c.constraint_name,
k.ordinal_position,
k.column_name
""")
# ORGANIZE, AND PICK ONE UNIQUE CONSTRAINT FOR LINKING
tables = UniqueIndex(keys=["name", "schema"])
for t, c in jx.groupby(raw_tables, ["table_name", "table_schema"]):
c = wrap(list(c))
best_index = Null
is_referenced = False
is_primary = False
for g, w in jx.groupby(c, "constraint_name"):
if not g.constraint_name:
continue
w = list(w)
ref = False
for r in relations:
if (r.table.name == t.table_name
and r.table.schema == t.table_schema
and r.constraint.name == g.constraint_name):
ref = True
is_prime = w[0].constraint_type == "PRIMARY"
reasons_this_one_is_better = [
best_index == None, # WE DO NOT HAVE A CANDIDATE YET
is_prime
and not is_primary, # PRIMARY KEYS ARE GOOD TO HAVE
is_primary == is_prime and ref and
not is_referenced, # REFERENCED UNIQUE TUPLES ARE GOOD TOO
is_primary == is_prime and ref == is_referenced and len(w)
< len(best_index), # THE SHORTER THE TUPLE, THE BETTER
]
if any(reasons_this_one_is_better):
is_primary = is_prime
is_referenced = ref
best_index = w
tables.add({
"name": t.table_name,
"schema": t.table_schema,
"id": [b.column_name for b in best_index],
})
fact_table = tables[self.settings.fact_table,
self.settings.database.schema]
ids_table = {
"alias": "t0",
"name": "__ids__",
"schema": fact_table.schema,
"id": fact_table.id,
}
relations.extend(
wrap({
"constraint": {
"name": "__link_ids_to_fact_table__"
},
"table": ids_table,
"column": {
"name": c
},
"referenced": {
"table": fact_table,
"column": {
"name": c
}
},
"ordinal_position": i,
}) for i, c in enumerate(fact_table.id))
tables.add(ids_table)
# GET ALL COLUMNS
raw_columns = self.db.query("""
SELECT
column_name,
table_schema,
table_name,
ordinal_position,
data_type
FROM
information_schema.columns
""")
reference_only_tables = [
r.split(".")[0] for r in self.settings.reference_only
if len(r.split(".")) == 2
]
reference_all_tables = [
r.split(".")[0] for r in self.settings.reference_only
if len(r.split(".")) == 1
]
foreign_column_table_schema_triples = {(r.column.name, r.table.name,
r.table.schema)
for r in relations}
referenced_column_table_schema_triples = {(
r.referenced.column.name,
r.referenced.table.name,
r.referenced.table.schema,
)
for r in relations}
related_column_table_schema_triples = (
foreign_column_table_schema_triples
| referenced_column_table_schema_triples)
columns = UniqueIndex(["column.name", "table.name", "table.schema"])
for c in raw_columns:
if c.table_name in reference_only_tables:
if c.table_name + "." + c.column_name in self.settings.reference_only:
include = True
reference = True
foreign = False
elif c.column_name in tables[(c.table_name,
c.table_schema)].id:
include = self.settings.show_foreign_keys
reference = False
foreign = False
else:
include = False
reference = False
foreign = False
elif c.table_name in reference_all_tables:
# TABLES USED FOR REFERENCE, NO NESTED DOCUMENTS EXPECTED
if c.column_name in tables[(c.table_name, c.table_schema)].id:
include = self.settings.show_foreign_keys
reference = True
foreign = False
elif (
c.column_name,
c.table_name,
c.table_schema,
) in foreign_column_table_schema_triples:
include = False
reference = False
foreign = True
else:
include = True
reference = False
foreign = False
elif c.column_name in tables[(c.table_name, c.table_schema)].id:
include = self.settings.show_foreign_keys
reference = False
foreign = False
elif (
c.column_name,
c.table_name,
c.table_schema,
) in foreign_column_table_schema_triples:
include = False
reference = False
foreign = True
elif (
c.column_name,
c.table_name,
c.table_schema,
) in referenced_column_table_schema_triples:
include = self.settings.show_foreign_keys
reference = False
foreign = False
else:
include = True
reference = False
foreign = False
rel = {
"column": {
"name": c.column_name,
"type": c.data_type
},
"table": {
"name": c.table_name,
"schema": c.table_schema
},
"ordinal_position": c.ordinal_position,
"is_id": c.column_name
in tables[(c.table_name, c.table_schema)].id,
"include": include, # TRUE IF THIS COLUMN IS OUTPUTTED
"reference":
reference, # TRUE IF THIS COLUMN REPRESENTS THE ROW
"foreign":
foreign, # TRUE IF THIS COLUMN POINTS TO ANOTHER ROW
}
columns.add(rel)
# ITERATE OVER ALL PATHS
todo = FlatList()
output_columns = FlatList()
nested_path_to_join = {}
all_nested_paths = [["."]]
def follow_paths(position, path, nested_path, done_relations,
no_nested_docs):
if position.name in self.settings.exclude:
return
if self.path_not_allowed(path):
return
if DEBUG:
Log.note("Trace {{path}}", path=path)
if position.name != "__ids__":
# USED TO CONFIRM WE CAN ACCESS THE TABLE (WILL THROW ERROR WHEN IF IT FAILS)
self.db.query(
ConcatSQL(
SQL_SELECT,
SQL_STAR,
SQL_FROM,
quote_column(position.schema, position.name),
SQL_LIMIT,
SQL_ONE,
))
if position.name in reference_all_tables:
no_nested_docs = True
if position.name in reference_only_tables:
return
curr_join_list = copy(nested_path_to_join[nested_path[0]])
###############################################################################
# INNER OBJECTS
###############################################################################
referenced_tables = list(
sort_using_key(
jx.groupby(
jx.filter(
relations,
{
"eq": {
"table.name": position.name,
"table.schema": position.schema,
}
},
),
"constraint.name",
),
key=lambda p: first(p[1]).column.name,
))
for g, constraint_columns in referenced_tables:
g = unwrap(g)
constraint_columns = deepcopy(constraint_columns)
if g["constraint.name"] in done_relations:
continue
if any(cc for cc in constraint_columns
if cc.referenced.table.name in self.settings.exclude):
continue
done_relations.add(g["constraint.name"])
many_to_one_joins = nested_path_to_join[nested_path[0]]
index = len(many_to_one_joins)
alias = "t" + text(index)
for c in constraint_columns:
c.referenced.table.alias = alias
c.table = position
many_to_one_joins.append({
"join_columns": constraint_columns,
"path": path,
"nested_path": nested_path,
})
# HANDLE THE COMMON *id SUFFIX
name = []
for cname, tname in zip(
constraint_columns.column.name,
constraint_columns.referenced.table.name,
):
if cname.startswith(tname):
name.append(tname)
elif cname.endswith("_id"):
name.append(cname[:-3])
else:
name.append(cname)
relation_string = many_to_one_string(constraint_columns[0])
step = "/".join(name)
if len(constraint_columns) == 1:
step = self.name_relations.get(relation_string, step)
referenced_column_path = concat_field(path, step)
if self.path_not_allowed(referenced_column_path):
continue
if referenced_column_path in reference_only_tables:
continue
col_pointer_name = relative_field(referenced_column_path,
nested_path[0])
for col in columns:
if (col.table.name
== constraint_columns[0].referenced.table.name
and col.table.schema
== constraint_columns[0].referenced.table.schema):
col_full_name = concat_field(
col_pointer_name, literal_field(col.column.name))
if (col.is_id and col.table.name == fact_table.name
and col.table.schema == fact_table.schema):
# ALWAYS SHOW THE ID OF THE FACT
c_index = len(output_columns)
output_columns.append({
"table_alias":
alias,
"column_alias":
"c" + text(c_index),
"column":
col,
"sort":
True,
"path":
referenced_column_path,
"nested_path":
nested_path,
"put":
col_full_name,
})
elif col.column.name == constraint_columns[
0].column.name:
c_index = len(output_columns)
output_columns.append({
"table_alias":
alias,
"column_alias":
"c" + text(c_index),
"column":
col,
"sort":
False,
"path":
referenced_column_path,
"nested_path":
nested_path,
"put":
col_full_name
if self.settings.show_foreign_keys else None,
})
elif col.is_id:
c_index = len(output_columns)
output_columns.append({
"table_alias":
alias,
"column_alias":
"c" + text(c_index),
"column":
col,
"sort":
False,
"path":
referenced_column_path,
"nested_path":
nested_path,
"put":
col_full_name
if self.settings.show_foreign_keys else None,
})
elif col.reference:
c_index = len(output_columns)
output_columns.append({
"table_alias":
alias,
"column_alias":
"c" + text(c_index),
"column":
col,
"sort":
False,
"path":
referenced_column_path,
"nested_path":
nested_path,
"put":
col_pointer_name
if not self.settings.show_foreign_keys else
col_full_name, # REFERENCE FIELDS CAN REPLACE THE WHOLE OBJECT BEING REFERENCED
})
elif col.include:
c_index = len(output_columns)
output_columns.append({
"table_alias":
alias,
"column_alias":
"c" + text(c_index),
"column":
col,
"sort":
False,
"path":
referenced_column_path,
"nested_path":
nested_path,
"put":
col_full_name,
})
if position.name in reference_only_tables:
continue
todo.append(
Data(
position=copy(constraint_columns[0].referenced.table),
path=referenced_column_path,
nested_path=nested_path,
done_relations=copy(done_relations),
no_nested_docs=no_nested_docs,
))
###############################################################################
# NESTED OBJECTS
###############################################################################
if not no_nested_docs:
nesting_tables = list(
sort_using_key(
jx.groupby(
jx.filter(
relations,
{
"eq": {
"referenced.table.name": position.name,
"referenced.table.schema":
position.schema,
}
},
),
"constraint.name",
),
key=lambda p: [(r.table.name, r.column.name)
for r in [first(p[1])]][0],
))
for g, constraint_columns in nesting_tables:
g = unwrap(g)
constraint_columns = deepcopy(constraint_columns)
if g["constraint.name"] in done_relations:
continue
done_relations.add(g["constraint.name"])
many_table = set(constraint_columns.table.name)
if not (many_table - self.settings.exclude):
continue
relation_string = one_to_many_string(constraint_columns[0])
step = "/".join(many_table)
if len(constraint_columns) == 1:
step = self.name_relations.get(relation_string, step)
referenced_column_path = concat_field(path, step)
if self.path_not_allowed(referenced_column_path):
continue
new_nested_path = [referenced_column_path] + nested_path
all_nested_paths.append(new_nested_path)
if referenced_column_path in nested_path_to_join:
Log.error(
"{{path}} already exists, try adding entry to name_relations",
path=referenced_column_path,
)
one_to_many_joins = nested_path_to_join[
referenced_column_path] = copy(curr_join_list)
index = len(one_to_many_joins)
alias = "t" + text(index)
for c in constraint_columns:
c.table.alias = alias
c.referenced.table = position
one_to_many_joins.append(
set_default(
{},
g,
{
"children": True,
"join_columns": constraint_columns,
"path": path,
"nested_path": nested_path,
},
))
for col in columns:
if (col.table.name == constraint_columns[0].table.name
and col.table.schema
== constraint_columns[0].table.schema):
col_full_name = join_field(
split_field(referenced_column_path)
[len(split_field(new_nested_path[0])):] +
[literal_field(col.column.name)])
if col.column.name == constraint_columns[
0].column.name:
c_index = len(output_columns)
output_columns.append({
"table_alias":
alias,
"column_alias":
"c" + text(c_index),
"column":
col,
"sort":
col.is_id,
"path":
referenced_column_path,
"nested_path":
new_nested_path,
"put":
col_full_name if
self.settings.show_foreign_keys else None,
})
elif col.is_id:
c_index = len(output_columns)
output_columns.append({
"table_alias":
alias,
"column_alias":
"c" + text(c_index),
"column":
col,
"sort":
col.is_id,
"path":
referenced_column_path,
"nested_path":
new_nested_path,
"put":
col_full_name if
self.settings.show_foreign_keys else None,
})
else:
c_index = len(output_columns)
output_columns.append({
"table_alias":
alias,
"column_alias":
"c" + text(c_index),
"column":
col,
"sort":
col.is_id,
"path":
referenced_column_path,
"nested_path":
new_nested_path,
"put":
col_full_name if col.include else None,
})
todo.append(
Data(
position=constraint_columns[0].table,
path=referenced_column_path,
nested_path=new_nested_path,
done_relations=copy(done_relations),
no_nested_docs=no_nested_docs,
))
path = "."
nested_path = [path]
nested_path_to_join["."] = [{
"path":
path,
"join_columns": [{
"referenced": {
"table": ids_table
}
}],
"nested_path":
nested_path,
}]
todo.append(
Data(
position=ids_table,
path=path,
nested_path=nested_path,
done_relations=set(),
no_nested_docs=False,
))
while todo:
item = todo.pop(0)
follow_paths(**item)
self.all_nested_paths = all_nested_paths
self.nested_path_to_join = nested_path_to_join
self.columns = output_columns
def query(self, query):
"""
:param query: JSON Query Expression, SET `format="container"` TO MAKE NEW TABLE OF RESULT
:return:
"""
if not startswith_field(query['from'], self.sf.fact_name):
Log.error("Expecting table, or some nested table")
query = QueryOp.wrap(query, self, self.namespace)
new_table = "temp_" + unique_name()
if query.format == "container":
create_table = "CREATE TABLE " + quote_column(new_table) + " AS "
else:
create_table = ""
if query.groupby and query.format != "cube":
op, index_to_columns = self._groupby_op(query, self.schema)
command = create_table + op
elif query.groupby:
query.edges, query.groupby = query.groupby, query.edges
op, index_to_columns = self._edges_op(query, self.schema)
command = create_table + op
query.edges, query.groupby = query.groupby, query.edges
elif query.edges or any(a != "none" for a in listwrap(query.select).aggregate):
op, index_to_columns = self._edges_op(query, self.schema)
command = create_table + op
else:
op = self._set_op(query)
return op
result = self.db.query(command)
if query.format == "container":
output = QueryTable(new_table, db=self.db, uid=self.uid, exists=True)
elif query.format == "cube" or (not query.format and query.edges):
column_names = [None] * (max(c.push_column for c in index_to_columns.values()) + 1)
for c in index_to_columns.values():
column_names[c.push_column] = c.push_column_name
if len(query.edges) == 0 and len(query.groupby) == 0:
data = {n: Data() for n in column_names}
for s in index_to_columns.values():
data[s.push_name][s.push_child] = unwrap(s.pull(result.data[0]))
if is_list(query.select):
select = [{"name": s.name} for s in query.select]
else:
select = {"name": query.select.name}
return Data(
data=unwrap(data),
select=select,
meta={"format": "cube"}
)
if not result.data:
edges = []
dims = []
for i, e in enumerate(query.edges + query.groupby):
allowNulls = coalesce(e.allowNulls, True)
if e.domain.type == "set" and e.domain.partitions:
domain = SimpleSetDomain(partitions=e.domain.partitions.name)
elif e.domain.type == "range":
domain = e.domain
elif is_op(e.value, TupleOp):
pulls = jx.sort([c for c in index_to_columns.values() if c.push_name == e.name],
"push_child").pull
parts = [tuple(p(d) for p in pulls) for d in result.data]
domain = SimpleSetDomain(partitions=jx.sort(set(parts)))
else:
domain = SimpleSetDomain(partitions=[])
dims.append(1 if allowNulls else 0)
edges.append(Data(
name=e.name,
allowNulls=allowNulls,
domain=domain
))
data = {}
for si, s in enumerate(listwrap(query.select)):
if s.aggregate == "count":
data[s.name] = Matrix(dims=dims, zeros=0)
else:
data[s.name] = Matrix(dims=dims)
if is_list(query.select):
select = [{"name": s.name} for s in query.select]
else:
select = {"name": query.select.name}
return Data(
meta={"format": "cube"},
edges=edges,
select=select,
data={k: v.cube for k, v in data.items()}
)
columns = None
edges = []
dims = []
for g in query.groupby:
g.is_groupby = True
for i, e in enumerate(query.edges + query.groupby):
allowNulls = coalesce(e.allowNulls, True)
if e.domain.type == "set" and e.domain.partitions:
domain = SimpleSetDomain(partitions=e.domain.partitions.name)
elif e.domain.type == "range":
domain = e.domain
elif e.domain.type == "time":
domain = wrap(mo_json.scrub(e.domain))
elif e.domain.type == "duration":
domain = wrap(mo_json.scrub(e.domain))
elif is_op(e.value, TupleOp):
pulls = jx.sort([c for c in index_to_columns.values() if c.push_name == e.name], "push_child").pull
parts = [tuple(p(d) for p in pulls) for d in result.data]
domain = SimpleSetDomain(partitions=jx.sort(set(parts)))
else:
if not columns:
columns = zip(*result.data)
parts = set(columns[i])
if e.is_groupby and None in parts:
allowNulls = True
parts -= {None}
if query.sort[i].sort == -1:
domain = SimpleSetDomain(partitions=wrap(sorted(parts, reverse=True)))
else:
domain = SimpleSetDomain(partitions=jx.sort(parts))
dims.append(len(domain.partitions) + (1 if allowNulls else 0))
edges.append(Data(
name=e.name,
allowNulls=allowNulls,
domain=domain
))
data_cubes = {}
for si, s in enumerate(listwrap(query.select)):
if s.aggregate == "count":
data_cubes[s.name] = Matrix(dims=dims, zeros=0)
else:
data_cubes[s.name] = Matrix(dims=dims)
r2c = index_to_coordinate(dims) # WORKS BECAUSE THE DATABASE SORTED THE EDGES TO CONFORM
for rownum, row in enumerate(result.data):
coord = r2c(rownum)
for i, s in enumerate(index_to_columns.values()):
if s.is_edge:
continue
if s.push_child == ".":
data_cubes[s.push_name][coord] = s.pull(row)
else:
data_cubes[s.push_name][coord][s.push_child] = s.pull(row)
if query.select == None:
select = Null
elif is_list(query.select):
select = [{"name": s.name} for s in query.select]
else:
select = {"name": query.select.name}
return Data(
meta={"format": "cube"},
edges=edges,
select=select,
data={k: v.cube for k, v in data_cubes.items()}
)
elif query.format == "table" or (not query.format and query.groupby):
column_names = [None] * (max(c.push_column for c in index_to_columns.values()) + 1)
for c in index_to_columns.values():
column_names[c.push_column] = c.push_column_name
data = []
for d in result.data:
row = [None for _ in column_names]
for s in index_to_columns.values():
if s.push_child == ".":
row[s.push_column] = s.pull(d)
elif s.num_push_columns:
tuple_value = row[s.push_column]
if tuple_value == None:
tuple_value = row[s.push_column] = [None] * s.num_push_columns
tuple_value[s.push_child] = s.pull(d)
elif row[s.push_column] == None:
row[s.push_column] = Data()
row[s.push_column][s.push_child] = s.pull(d)
else:
row[s.push_column][s.push_child] = s.pull(d)
data.append(tuple(unwrap(r) for r in row))
output = Data(
meta={"format": "table"},
header=column_names,
data=data
)
elif query.format == "list" or (not query.edges and not query.groupby):
if not query.edges and not query.groupby and any(listwrap(query.select).aggregate):
if is_list(query.select):
data = Data()
for c in index_to_columns.values():
if c.push_child == ".":
if data[c.push_name] == None:
data[c.push_name] = c.pull(result.data[0])
elif is_list(data[c.push_name]):
data[c.push_name].append(c.pull(result.data[0]))
else:
data[c.push_name] = [data[c.push_name], c.pull(result.data[0])]
else:
data[c.push_name][c.push_child] = c.pull(result.data[0])
output = Data(
meta={"format": "value"},
data=data
)
else:
data = Data()
for s in index_to_columns.values():
if not data[s.push_child]:
data[s.push_child] = s.pull(result.data[0])
else:
data[s.push_child] += [s.pull(result.data[0])]
output = Data(
meta={"format": "value"},
data=unwrap(data)
)
else:
data = []
for rownum in result.data:
row = Data()
for c in index_to_columns.values():
if c.push_child == ".":
row[c.push_name] = c.pull(rownum)
elif c.num_push_columns:
tuple_value = row[c.push_name]
if not tuple_value:
tuple_value = row[c.push_name] = [None] * c.num_push_columns
tuple_value[c.push_child] = c.pull(rownum)
else:
row[c.push_name][c.push_child] = c.pull(rownum)
data.append(row)
output = Data(
meta={"format": "list"},
data=data
)
else:
Log.error("unknown format {{format}}", format=query.format)
return output
def streamer():
for row in self.cursor:
output = Data()
for c, v in zip(columns, row):
output[c] = v
yield output
class PersistentQueue(object):
"""
THREAD-SAFE, PERSISTENT QUEUE
CAN HANDLE MANY PRODUCERS, BUT THE pop(), commit() IDIOM CAN HANDLE ONLY
ONE CONSUMER.
IT IS IMPORTANT YOU commit() or close(), OTHERWISE NOTHING COMES OFF THE QUEUE
"""
def __init__(self, _file):
"""
file - USES FILE FOR PERSISTENCE
"""
self.file = File.new_instance(_file)
self.lock = Lock("lock for persistent queue using file " + self.file.name)
self.please_stop = Signal()
self.db = Data()
self.pending = []
if self.file.exists:
for line in self.file:
with suppress_exception:
delta = mo_json.json2value(line)
apply_delta(self.db, delta)
if self.db.status.start == None: # HAPPENS WHEN ONLY ADDED TO QUEUE, THEN CRASH
self.db.status.start = 0
self.start = self.db.status.start
# SCRUB LOST VALUES
lost = 0
for k in self.db.keys():
with suppress_exception:
if k!="status" and int(k) < self.start:
self.db[k] = None
lost += 1
# HAPPENS FOR self.db.status, BUT MAYBE OTHER PROPERTIES TOO
if lost:
Log.warning("queue file had {{num}} items lost", num= lost)
DEBUG and Log.note("Persistent queue {{name}} found with {{num}} items", name=self.file.abspath, num=len(self))
else:
self.db.status = Data(
start=0,
end=0
)
self.start = self.db.status.start
DEBUG and Log.note("New persistent queue {{name}}", name=self.file.abspath)
def _add_pending(self, delta):
delta = wrap(delta)
self.pending.append(delta)
def _apply_pending(self):
for delta in self.pending:
apply_delta(self.db, delta)
self.pending = []
def __iter__(self):
"""
BLOCKING ITERATOR
"""
while not self.please_stop:
try:
value = self.pop()
if value is not THREAD_STOP:
yield value
except Exception as e:
Log.warning("Tell me about what happened here", cause=e)
def add(self, value):
with self.lock:
if self.closed:
Log.error("Queue is closed")
if value is THREAD_STOP:
DEBUG and Log.note("Stop is seen in persistent queue")
self.please_stop.go()
return
self._add_pending({"add": {str(self.db.status.end): value}})
self.db.status.end += 1
self._add_pending({"add": {"status.end": self.db.status.end}})
self._commit()
return self
def __len__(self):
with self.lock:
return self.db.status.end - self.start
def __getitem__(self, item):
return self.db[str(item + self.start)]
def pop(self, timeout=None):
"""
:param timeout: OPTIONAL DURATION
:return: None, IF timeout PASSES
"""
with self.lock:
while not self.please_stop:
if self.db.status.end > self.start:
value = self.db[str(self.start)]
self.start += 1
return value
if timeout is not None:
with suppress_exception:
self.lock.wait(timeout=timeout)
if self.db.status.end <= self.start:
return None
else:
self.lock.wait()
DEBUG and Log.note("persistent queue already stopped")
return THREAD_STOP
def pop_all(self):
"""
NON-BLOCKING POP ALL IN QUEUE, IF ANY
"""
with self.lock:
if self.please_stop:
return [THREAD_STOP]
if self.db.status.end == self.start:
return []
output = []
for i in range(self.start, self.db.status.end):
output.append(self.db[str(i)])
self.start = self.db.status.end
return output
def rollback(self):
with self.lock:
if self.closed:
return
self.start = self.db.status.start
self.pending = []
def commit(self):
with self.lock:
if self.closed:
Log.error("Queue is closed, commit not allowed")
try:
self._add_pending({"add": {"status.start": self.start}})
for i in range(self.db.status.start, self.start):
self._add_pending({"remove": str(i)})
if self.db.status.end - self.start < 10 or Random.range(0, 1000) == 0: # FORCE RE-WRITE TO LIMIT FILE SIZE
# SIMPLY RE-WRITE FILE
if DEBUG:
Log.note("Re-write {{num_keys}} keys to persistent queue", num_keys=self.db.status.end - self.start)
for k in self.db.keys():
if k == "status" or int(k) >= self.db.status.start:
continue
Log.error("Not expecting {{key}}", key=k)
self._commit()
self.file.write(mo_json.value2json({"add": self.db}) + "\n")
else:
self._commit()
except Exception as e:
raise e
def _commit(self):
self.file.append("\n".join(mo_json.value2json(p) for p in self.pending))
self._apply_pending()
def close(self):
self.please_stop.go()
with self.lock:
if self.db is None:
return
self.add(THREAD_STOP)
if self.db.status.end == self.start:
DEBUG and Log.note("persistent queue clear and closed")
self.file.delete()
else:
DEBUG and Log.note("persistent queue closed with {{num}} items left", num=len(self))
try:
self._add_pending({"add": {"status.start": self.start}})
for i in range(self.db.status.start, self.start):
self._add_pending({"remove": str(i)})
self.file.write(mo_json.value2json({"add": self.db}) + "\n" + ("\n".join(mo_json.value2json(p) for p in self.pending)) + "\n")
self._apply_pending()
except Exception as e:
raise e
self.db = None
@property
def closed(self):
with self.lock:
return self.db is None
def construct_docs(self, cursor, append, please_stop):
"""
:param cursor: ITERATOR OF RECORDS
:param append: METHOD TO CALL WITH CONSTRUCTED DOCUMENT
:return: (count, first, next, next_key)
number of documents added
the first document in the batch
the first document of the next batch
"""
null_values = set(self.settings.snowflake.null_values) | {None}
count = 0
rownum = 0
columns = tuple(wrap(c) for c in self.schema.columns)
with Timer("Downloading from MySQL"):
curr_record = Null
for rownum, row in enumerate(cursor):
if please_stop:
Log.error("Got `please_stop` signal")
nested_path = []
next_record = None
for c, value in zip(columns, row):
if value in null_values:
continue
if len(nested_path) < len(c.nested_path):
nested_path = unwrap(c.nested_path)
next_record = Data()
next_record[c.put] = value
if len(nested_path) > 1:
path = nested_path[-2]
children = curr_record[path]
if children == None:
children = curr_record[path] = wrap([])
if len(nested_path) > 2:
parent_path = path
for path in list(reversed(nested_path[0:-2:])):
parent = children.last()
relative_path = relative_field(path, parent_path)
children = parent[relative_path]
if children == None:
children = parent[relative_path] = wrap([])
parent_path = path
children.append(next_record)
continue
if curr_record == next_record:
Log.error("not expected")
if curr_record:
append(curr_record["id"], count)
count += 1
curr_record = next_record
# DEAL WITH LAST RECORD
if curr_record:
append(curr_record["id"], count)
count += 1
Log.note("{{num}} documents ({{rownum}} db records)",
num=count,
rownum=rownum)
def life_cycle_watcher(please_stop):
bad_requests = Data()
setup_threads = []
last_get = Date.now()
setup_in_progress = set()
while not please_stop:
spot_requests = self._get_managed_spot_requests()
instances = wrap({
i.id: i
for r in self.ec2_conn.get_all_instances()
for i in r.instances
})
# INSTANCES THAT REQUIRE SETUP
time_to_stop_trying = {}
please_setup = [
(i, r) for i, r in [(instances[r.instance_id], r)
for r in spot_requests]
if i.id and (not i.tags.get("Name") or i.tags.get(
"Name") == self.settings.ec2.instance.name +
" (setup)") and i.id not in setup_in_progress
and i._state.name == "running"
and Date.now() > Date(i.launch_time) + DELAY_BEFORE_SETUP
]
for i, r in please_setup:
if not time_to_stop_trying.get(i.id):
time_to_stop_trying[
i.id] = Date.now() + TIME_FROM_RUNNING_TO_LOGIN
if Date.now() > time_to_stop_trying[i.id]:
# FAIL TO SETUP AFTER x MINUTES, THEN TERMINATE INSTANCE
self.ec2_conn.terminate_instances(instance_ids=[i.id])
with self.net_new_locker:
self.net_new_spot_requests.remove(r.id)
Log.warning(
"Problem with setup of {{instance_id}}. Time is up. Instance TERMINATED!",
instance_id=i.id)
continue
try:
p = self.settings.utility[i.instance_type]
if p == None:
try:
self.ec2_conn.terminate_instances(
instance_ids=[i.id])
with self.net_new_locker:
self.net_new_spot_requests.remove(r.id)
finally:
Log.error(
"Can not setup unknown {{instance_id}} of type {{type}}",
instance_id=i.id,
type=i.instance_type)
i.markup = p
i.add_tag("Name",
self.settings.ec2.instance.name + " (setup)")
setup_in_progress.add(i.id)
t = Thread.run("setup for " + text(i.id), track_setup,
self.instance_manager.setup, r, i, p)
if SINGLE_THREAD_SETUP:
t.join()
setup_threads.append(t)
except Exception as e:
i.add_tag("Name", "")
Log.warning("Unexpected failure on startup",
instance_id=i.id,
cause=e)
if Date.now() - last_get > 5 * SECOND:
# REFRESH STALE
spot_requests = self._get_managed_spot_requests()
last_get = Date.now()
pending = wrap([
r for r in spot_requests
if r.status.code in PENDING_STATUS_CODES
])
give_up = wrap([
r for r in spot_requests
if (r.status.code in PROBABLY_NOT_FOR_A_WHILE
| TERMINATED_STATUS_CODES) and r.id not in bad_requests
])
ignore = wrap([
r for r in spot_requests if r.status.code in MIGHT_HAPPEN
]) # MIGHT HAPPEN, BUT NO NEED TO WAIT FOR IT
if self.done_making_new_spot_requests:
with self.net_new_locker:
expired = Date.now(
) - self.settings.run_interval + 2 * MINUTE
for ii in list(self.net_new_spot_requests):
if Date(ii.create_time) < expired:
# SOMETIMES REQUESTS NEVER GET INTO THE MAIN LIST OF REQUESTS
self.net_new_spot_requests.remove(ii)
for g in ignore:
self.net_new_spot_requests.remove(g.id)
pending = UniqueIndex(("id", ), data=pending)
pending = pending | self.net_new_spot_requests
if give_up:
self.ec2_conn.cancel_spot_instance_requests(
request_ids=give_up.id)
Log.note(
"Cancelled spot requests {{spots}}, {{reasons}}",
spots=give_up.id,
reasons=give_up.status.code)
for g in give_up:
bad_requests[g.id] += 1
if g.id in self.net_new_spot_requests:
self.net_new_spot_requests.remove(g.id)
if g.status.code == "capacity-not-available":
self.no_capacity[
g.launch_specification.
instance_type] = Date.now()
if g.status.code == "bad-parameters":
self.no_capacity[
g.launch_specification.
instance_type] = Date.now()
Log.warning(
"bad parameters while requesting type {{type}}",
type=g.launch_specification.
instance_type)
if not pending and self.done_making_new_spot_requests:
Log.note("No more pending spot requests")
break
elif pending:
Log.note("waiting for spot requests: {{pending}}",
pending=[p.id for p in pending])
(Till(seconds=10) | please_stop).wait()
with Timer("Save no capacity to file"):
table = [{
"instance_type": k,
"last_failure": v
} for k, v in self.no_capacity.items()]
self.no_capacity_file.write(value2json(table, pretty=True))
# WAIT FOR SETUP TO COMPLETE
for t in setup_threads:
t.join()
Log.note("life cycle watcher has stopped")
def query_metadata(self, query):
frum, query['from'] = query['from'], self
schema = self.sf.tables["."].schema
query = QueryOp.wrap(query, schema)
columns = self.sf.columns
where = query.where
table_name = None
column_name = None
if query.edges or query.groupby:
Log.error("Aggregates(groupby or edge) are not supported")
if where.op == "eq" and where.lhs.var == "table":
table_name = mo_json.json2value(where.rhs.json)
elif where.op == "eq" and where.lhs.var == "name":
column_name = mo_json.json2value(where.rhs.json)
else:
Log.error("Only simple filters are expected like: \"eq\" on table and column name")
tables = [concat_field(self.sf.fact_name, i) for i in self.tables.keys()]
metadata = []
if columns[-1].es_column != GUID:
columns.append(Column(
name=GUID,
jx_type=STRING,
es_column=GUID,
es_index=self.sf.fact_name,
nested_path=["."]
))
for tname, table in zip(t, tables):
if table_name != None and table_name != table:
continue
for col in columns:
cname, ctype = untyped_column(col.es_column)
if column_name != None and column_name != cname:
continue
metadata.append((table, relative_field(col.name, tname), col.type, unwraplist(col.nested_path)))
if query.format == "cube":
num_rows = len(metadata)
header = ["table", "name", "type", "nested_path"]
temp_data = dict(zip(header, zip(*metadata)))
return Data(
meta={"format": "cube"},
data=temp_data,
edges=[{
"name": "rownum",
"domain": {
"type": "rownum",
"min": 0,
"max": num_rows,
"interval": 1
}
}]
)
elif query.format == "table":
header = ["table", "name", "type", "nested_path"]
return Data(
meta={"format": "table"},
header=header,
data=metadata
)
else:
header = ["table", "name", "type", "nested_path"]
return Data(
meta={"format": "list"},
data=[dict(zip(header, r)) for r in metadata]
)
def _update_cardinality(self, column):
"""
QUERY ES TO FIND CARDINALITY AND PARTITIONS FOR A SIMPLE COLUMN
"""
if column.es_index in self.index_does_not_exist:
return
if column.jx_type in STRUCT:
Log.error("not supported")
try:
if column.es_index == "meta.columns":
partitions = jx.sort([g[column.es_column] for g, _ in jx.groupby(self.meta.columns, column.es_column) if g[column.es_column] != None])
self.meta.columns.update({
"set": {
"partitions": partitions,
"count": len(self.meta.columns),
"cardinality": len(partitions),
"multi": 1,
"last_updated": Date.now()
},
"where": {"eq": {"es_index": column.es_index, "es_column": column.es_column}}
})
return
if column.es_index == "meta.tables":
partitions = jx.sort([g[column.es_column] for g, _ in jx.groupby(self.meta.tables, column.es_column) if g[column.es_column] != None])
self.meta.columns.update({
"set": {
"partitions": partitions,
"count": len(self.meta.tables),
"cardinality": len(partitions),
"multi": 1,
"last_updated": Date.now()
},
"where": {"eq": {"es_index": column.es_index, "es_column": column.es_column}}
})
return
es_index = column.es_index.split(".")[0]
is_text = [cc for cc in self.meta.columns if cc.es_column == column.es_column and cc.es_type == "text"]
if is_text:
# text IS A MULTIVALUE STRING THAT CAN ONLY BE FILTERED
result = self.es_cluster.post("/" + es_index + "/_search", data={
"aggs": {
"count": {"filter": {"match_all": {}}}
},
"size": 0
})
count = result.hits.total
cardinality = max(1001, count)
multi = 1001
elif column.es_column == "_id":
result = self.es_cluster.post("/" + es_index + "/_search", data={
"query": {"match_all": {}},
"size": 0
})
count = cardinality = result.hits.total
multi = 1
elif column.es_type == BOOLEAN:
result = self.es_cluster.post("/" + es_index + "/_search", data={
"aggs": {
"count": _counting_query(column)
},
"size": 0
})
count = result.hits.total
cardinality = 2
multi = 1
else:
result = self.es_cluster.post("/" + es_index + "/_search", data={
"aggs": {
"count": _counting_query(column),
"multi": {"max": {"script": "doc[" + quote(column.es_column) + "].values.size()"}}
},
"size": 0
})
agg_results = result.aggregations
count = result.hits.total
cardinality = coalesce(agg_results.count.value, agg_results.count._nested.value, agg_results.count.doc_count)
multi = int(coalesce(agg_results.multi.value, 1))
if cardinality == None:
Log.error("logic error")
query = Data(size=0)
if column.es_column == "_id":
self.meta.columns.update({
"set": {
"count": cardinality,
"cardinality": cardinality,
"multi": 1,
"last_updated": Date.now()
},
"clear": ["partitions"],
"where": {"eq": {"es_index": column.es_index, "es_column": column.es_column}}
})
return
elif cardinality > 1000 or (count >= 30 and cardinality == count) or (count >= 1000 and cardinality / count > 0.99):
DEBUG and Log.note("{{table}}.{{field}} has {{num}} parts", table=column.es_index, field=column.es_column, num=cardinality)
self.meta.columns.update({
"set": {
"count": count,
"cardinality": cardinality,
"multi": multi,
"last_updated": Date.now()
},
"clear": ["partitions"],
"where": {"eq": {"es_index": column.es_index, "es_column": column.es_column}}
})
return
elif column.es_type in elasticsearch.ES_NUMERIC_TYPES and cardinality > 30:
DEBUG and Log.note("{{table}}.{{field}} has {{num}} parts", table=column.es_index, field=column.es_column, num=cardinality)
self.meta.columns.update({
"set": {
"count": count,
"cardinality": cardinality,
"multi": multi,
"last_updated": Date.now()
},
"clear": ["partitions"],
"where": {"eq": {"es_index": column.es_index, "es_column": column.es_column}}
})
return
elif len(column.nested_path) != 1:
query.aggs["_"] = {
"nested": {"path": column.nested_path[0]},
"aggs": {"_nested": {"terms": {"field": column.es_column}}}
}
elif cardinality == 0:
query.aggs["_"] = {"terms": {"field": column.es_column}}
else:
query.aggs["_"] = {"terms": {"field": column.es_column, "size": cardinality}}
result = self.es_cluster.post("/" + es_index + "/_search", data=query)
aggs = result.aggregations._
if aggs._nested:
parts = jx.sort(aggs._nested.buckets.key)
else:
parts = jx.sort(aggs.buckets.key)
self.meta.columns.update({
"set": {
"count": count,
"cardinality": cardinality,
"multi": multi,
"partitions": parts,
"last_updated": Date.now()
},
"where": {"eq": {"es_index": column.es_index, "es_column": column.es_column}}
})
except Exception as e:
# CAN NOT IMPORT: THE TEST MODULES SETS UP LOGGING
# from tests.test_jx import TEST_TABLE
e = Except.wrap(e)
TEST_TABLE = "testdata"
is_missing_index = any(w in e for w in ["IndexMissingException", "index_not_found_exception"])
is_test_table = column.es_index.startswith((TEST_TABLE_PREFIX, TEST_TABLE))
if is_missing_index and is_test_table:
# WE EXPECT TEST TABLES TO DISAPPEAR
self.meta.columns.update({
"clear": ".",
"where": {"eq": {"es_index": column.es_index}}
})
self.index_does_not_exist.add(column.es_index)
else:
self.meta.columns.update({
"set": {
"last_updated": Date.now()
},
"clear": [
"count",
"cardinality",
"multi",
"partitions",
],
"where": {"eq": {"es_index": column.es_index, "es_column": column.es_column}}
})
Log.warning("Could not get {{col.es_index}}.{{col.es_column}} info", col=column, cause=e)
class PersistentQueue(object):
"""
THREAD-SAFE, PERSISTENT QUEUE
CAN HANDLE MANY PRODUCERS, BUT THE pop(), commit() IDIOM CAN HANDLE ONLY
ONE CONSUMER.
IT IS IMPORTANT YOU commit() or close(), OTHERWISE NOTHING COMES OFF THE QUEUE
"""
def __init__(self, _file):
"""
file - USES FILE FOR PERSISTENCE
"""
self.file = File.new_instance(_file)
self.lock = Lock("lock for persistent queue using file " +
self.file.name)
self.please_stop = Signal()
self.db = Data()
self.pending = []
if self.file.exists:
for line in self.file:
with suppress_exception:
delta = mo_json.json2value(line)
apply_delta(self.db, delta)
if self.db.status.start == None: # HAPPENS WHEN ONLY ADDED TO QUEUE, THEN CRASH
self.db.status.start = 0
self.start = self.db.status.start
# SCRUB LOST VALUES
lost = 0
for k in self.db.keys():
with suppress_exception:
if k != "status" and int(k) < self.start:
self.db[k] = None
lost += 1
# HAPPENS FOR self.db.status, BUT MAYBE OTHER PROPERTIES TOO
if lost:
Log.warning("queue file had {{num}} items lost", num=lost)
if DEBUG:
Log.note("Persistent queue {{name}} found with {{num}} items",
name=self.file.abspath,
num=len(self))
else:
self.db.status = Data(start=0, end=0)
self.start = self.db.status.start
if DEBUG:
Log.note("New persistent queue {{name}}",
name=self.file.abspath)
def _add_pending(self, delta):
delta = wrap(delta)
self.pending.append(delta)
def _apply_pending(self):
for delta in self.pending:
apply_delta(self.db, delta)
self.pending = []
def __iter__(self):
"""
BLOCKING ITERATOR
"""
while not self.please_stop:
try:
value = self.pop()
if value is not THREAD_STOP:
yield value
except Exception as e:
Log.warning("Tell me about what happened here", cause=e)
if DEBUG:
Log.note("queue iterator is done")
def add(self, value):
with self.lock:
if self.closed:
Log.error("Queue is closed")
if value is THREAD_STOP:
if DEBUG:
Log.note("Stop is seen in persistent queue")
self.please_stop.go()
return
self._add_pending({"add": {str(self.db.status.end): value}})
self.db.status.end += 1
self._add_pending({"add": {"status.end": self.db.status.end}})
self._commit()
return self
def __len__(self):
with self.lock:
return self.db.status.end - self.start
def __getitem__(self, item):
return self.db[str(item + self.start)]
def pop(self, timeout=None):
"""
:param timeout: OPTIONAL DURATION
:return: None, IF timeout PASSES
"""
with self.lock:
while not self.please_stop:
if self.db.status.end > self.start:
value = self.db[str(self.start)]
self.start += 1
return value
if timeout is not None:
with suppress_exception:
self.lock.wait(timeout=timeout)
if self.db.status.end <= self.start:
return None
else:
self.lock.wait()
if DEBUG:
Log.note("persistent queue already stopped")
return THREAD_STOP
def pop_all(self):
"""
NON-BLOCKING POP ALL IN QUEUE, IF ANY
"""
with self.lock:
if self.please_stop:
return [THREAD_STOP]
if self.db.status.end == self.start:
return []
output = []
for i in range(self.start, self.db.status.end):
output.append(self.db[str(i)])
self.start = self.db.status.end
return output
def rollback(self):
with self.lock:
if self.closed:
return
self.start = self.db.status.start
self.pending = []
def commit(self):
with self.lock:
if self.closed:
Log.error("Queue is closed, commit not allowed")
try:
self._add_pending({"add": {"status.start": self.start}})
for i in range(self.db.status.start, self.start):
self._add_pending({"remove": str(i)})
if self.db.status.end - self.start < 10 or Random.range(
0, 1000) == 0: # FORCE RE-WRITE TO LIMIT FILE SIZE
# SIMPLY RE-WRITE FILE
if DEBUG:
Log.note(
"Re-write {{num_keys}} keys to persistent queue",
num_keys=self.db.status.end - self.start)
for k in self.db.keys():
if k == "status" or int(k) >= self.db.status.start:
continue
Log.error("Not expecting {{key}}", key=k)
self._commit()
self.file.write(
mo_json.value2json({"add": self.db}) + "\n")
else:
self._commit()
except Exception as e:
raise e
def _commit(self):
self.file.append("\n".join(
mo_json.value2json(p) for p in self.pending))
self._apply_pending()
def close(self):
self.please_stop.go()
with self.lock:
if self.db is None:
return
self.add(THREAD_STOP)
if self.db.status.end == self.start:
if DEBUG:
Log.note("persistent queue clear and closed")
self.file.delete()
else:
if DEBUG:
Log.note("persistent queue closed with {{num}} items left",
num=len(self))
try:
self._add_pending({"add": {"status.start": self.start}})
for i in range(self.db.status.start, self.start):
self._add_pending({"remove": str(i)})
self.file.write(
mo_json.value2json({"add": self.db}) + "\n" +
("\n".join(
mo_json.value2json(p)
for p in self.pending)) + "\n")
self._apply_pending()
except Exception as e:
raise e
self.db = None
@property
def closed(self):
with self.lock:
return self.db is None
def format_list(decoders, aggs, start, query, select):
new_edges = count_dim(aggs, decoders)
def data():
dims = tuple(
len(e.domain.partitions) + (0 if e.allowNulls is False else 1)
for e in new_edges)
is_sent = Matrix(dims=dims, zeros=0)
if query.sort and not query.groupby:
# TODO: USE THE format_table() TO PRODUCE THE NEEDED VALUES INSTEAD OF DUPLICATING LOGIC HERE
all_coord = is_sent._all_combos(
) # TRACK THE EXPECTED COMBINATIONS
for _, coord, agg in aggs_iterator(aggs, decoders):
missing_coord = all_coord.next()
while coord != missing_coord:
# INSERT THE MISSING COORDINATE INTO THE GENERATION
output = Data()
for i, d in enumerate(decoders):
output[query.edges[i].name] = d.get_value(
missing_coord[i])
for s in select:
if s.aggregate == "count":
output[s.name] = 0
yield output
missing_coord = all_coord.next()
output = Data()
for e, c, d in zip(query.edges, coord, decoders):
output[e.name] = d.get_value(c)
for s in select:
output[s.name] = s.pull(agg)
yield output
else:
for row, coord, agg in aggs_iterator(aggs, decoders):
is_sent[coord] = 1
output = Data()
for e, c, d in zip(query.edges, coord, decoders):
output[e.name] = d.get_value(c)
for s in select:
output[s.name] = s.pull(agg)
yield output
# EMIT THE MISSING CELLS IN THE CUBE
if not query.groupby:
for c, v in is_sent:
if not v:
output = Data()
for i, d in enumerate(decoders):
output[query.edges[i].name] = d.get_value(c[i])
for s in select:
if s.aggregate == "count":
output[s.name] = 0
yield output
output = Data(meta={"format": "list"}, data=list(data()))
return output
def __data__(self):
output = Data({k:getattr(self,k) for k in vars(self)})
output.cause=unwraplist([c.__data__() for c in listwrap(output.cause)])
return output
def get_more(please_stop):
more.append(
es.search(
Data(query=more_filter, stored_fields=es_query.stored_fields)))
elif depth == 1:
return _MAX(cube)
else:
return _MAX(_max(depth - 1, c) for c in cube)
def _min(depth, cube):
if depth == 0:
return cube
elif depth == 1:
return _MIN(cube)
else:
return _MIN(_min(depth - 1, c) for c in cube)
aggregates = Data(max=_max, maximum=_max, min=_min, minimum=_min)
def _iter(cube, depth):
if depth == 1:
return cube.__iter__()
else:
def iterator():
for c in cube:
for b in _iter(c, depth - 1):
yield b
return iterator()
def es_aggsop(es, frum, query):
query = query.copy() # WE WILL MARK UP THIS QUERY
schema = frum.schema
select = listwrap(query.select)
es_query = Data()
new_select = Data(
) # MAP FROM canonical_name (USED FOR NAMES IN QUERY) TO SELECT MAPPING
formula = []
for s in select:
if s.aggregate == "count" and isinstance(
s.value, Variable) and s.value.var == ".":
if schema.query_path == ".":
s.pull = jx_expression_to_function("doc_count")
else:
s.pull = jx_expression_to_function(
{"coalesce": ["_nested.doc_count", "doc_count", 0]})
elif isinstance(s.value, Variable):
if s.aggregate == "count":
new_select["count_" + literal_field(s.value.var)] += [s]
else:
new_select[literal_field(s.value.var)] += [s]
elif s.aggregate:
formula.append(s)
for canonical_name, many in new_select.items():
for s in many:
es_cols = frum.schema.values(s.value.var)
if s.aggregate == "count":
canonical_names = []
for es_col in es_cols:
cn = literal_field(es_col.es_column + "_count")
if es_col.type == EXISTS:
canonical_names.append(cn + ".doc_count")
es_query.aggs[cn].filter.range = {
es_col.es_column: {
"gt": 0
}
}
else:
canonical_names.append(cn + ".value")
es_query.aggs[cn].value_count.field = es_col.es_column
if len(es_cols) == 1:
s.pull = jx_expression_to_function(canonical_names[0])
else:
s.pull = jx_expression_to_function(
{"add": canonical_names})
elif s.aggregate == "median":
if len(es_cols) > 1:
Log.error(
"Do not know how to count columns with more than one type (script probably)"
)
# ES USES DIFFERENT METHOD FOR PERCENTILES
key = literal_field(canonical_name + " percentile")
es_query.aggs[key].percentiles.field = es_cols[0].es_column
es_query.aggs[key].percentiles.percents += [50]
s.pull = jx_expression_to_function(key + ".values.50\.0")
elif s.aggregate == "percentile":
if len(es_cols) > 1:
Log.error(
"Do not know how to count columns with more than one type (script probably)"
)
# ES USES DIFFERENT METHOD FOR PERCENTILES
key = literal_field(canonical_name + " percentile")
if isinstance(
s.percentile,
text_type) or s.percetile < 0 or 1 < s.percentile:
Log.error(
"Expecting percentile to be a float from 0.0 to 1.0")
percent = Math.round(s.percentile * 100, decimal=6)
es_query.aggs[key].percentiles.field = es_cols[0].es_column
es_query.aggs[key].percentiles.percents += [percent]
s.pull = jx_expression_to_function(
key + ".values." + literal_field(text_type(percent)))
elif s.aggregate == "cardinality":
canonical_names = []
for es_col in es_cols:
cn = literal_field(es_col.es_column + "_cardinality")
canonical_names.append(cn)
es_query.aggs[cn].cardinality.field = es_col.es_column
if len(es_cols) == 1:
s.pull = jx_expression_to_function(canonical_names[0] +
".value")
else:
s.pull = jx_expression_to_function({
"add": [cn + ".value" for cn in canonical_names],
"default":
0
})
elif s.aggregate == "stats":
if len(es_cols) > 1:
Log.error(
"Do not know how to count columns with more than one type (script probably)"
)
# REGULAR STATS
stats_name = literal_field(canonical_name)
es_query.aggs[stats_name].extended_stats.field = es_cols[
0].es_column
# GET MEDIAN TOO!
median_name = literal_field(canonical_name + "_percentile")
es_query.aggs[median_name].percentiles.field = es_cols[
0].es_column
es_query.aggs[median_name].percentiles.percents += [50]
s.pull = get_pull_stats(stats_name, median_name)
elif s.aggregate == "union":
pulls = []
for es_col in es_cols:
script = {
"scripted_metric": {
'init_script':
'params._agg.terms = new HashSet()',
'map_script':
'for (v in doc[' + quote(es_col.es_column) +
'].values) params._agg.terms.add(v)',
'combine_script':
'return params._agg.terms.toArray()',
'reduce_script':
'HashSet output = new HashSet(); for (a in params._aggs) { if (a!=null) for (v in a) {output.add(v)} } return output.toArray()',
}
}
stats_name = encode_property(es_col.es_column)
if es_col.nested_path[0] == ".":
es_query.aggs[stats_name] = script
pulls.append(
jx_expression_to_function(stats_name + ".value"))
else:
es_query.aggs[stats_name] = {
"nested": {
"path": es_col.nested_path[0]
},
"aggs": {
"_nested": script
}
}
pulls.append(
jx_expression_to_function(stats_name +
"._nested.value"))
if len(pulls) == 0:
s.pull = NULL
elif len(pulls) == 1:
s.pull = pulls[0]
else:
s.pull = lambda row: UNION(p(row) for p in pulls)
else:
if len(es_cols) > 1:
Log.error(
"Do not know how to count columns with more than one type (script probably)"
)
# PULL VALUE OUT OF THE stats AGGREGATE
es_query.aggs[literal_field(
canonical_name
)].extended_stats.field = es_cols[0].es_column
s.pull = jx_expression_to_function({
"coalesce": [
literal_field(canonical_name) + "." +
aggregates[s.aggregate], s.default
]
})
for i, s in enumerate(formula):
canonical_name = literal_field(s.name)
if isinstance(s.value, TupleOp):
if s.aggregate == "count":
# TUPLES ALWAYS EXIST, SO COUNTING THEM IS EASY
s.pull = "doc_count"
else:
Log.error("{{agg}} is not a supported aggregate over a tuple",
agg=s.aggregate)
elif s.aggregate == "count":
es_query.aggs[literal_field(
canonical_name)].value_count.script = s.value.partial_eval(
).to_painless(schema).script(schema)
s.pull = jx_expression_to_function(
literal_field(canonical_name) + ".value")
elif s.aggregate == "median":
# ES USES DIFFERENT METHOD FOR PERCENTILES THAN FOR STATS AND COUNT
key = literal_field(canonical_name + " percentile")
es_query.aggs[key].percentiles.script = s.value.to_painless(
schema).script(schema)
es_query.aggs[key].percentiles.percents += [50]
s.pull = jx_expression_to_function(key + ".values.50\.0")
elif s.aggregate == "percentile":
# ES USES DIFFERENT METHOD FOR PERCENTILES THAN FOR STATS AND COUNT
key = literal_field(canonical_name + " percentile")
percent = Math.round(s.percentile * 100, decimal=6)
es_query.aggs[key].percentiles.script = s.value.to_painless(
schema).script(schema)
es_query.aggs[key].percentiles.percents += [percent]
s.pull = jx_expression_to_function(
key + ".values." + literal_field(text_type(percent)))
elif s.aggregate == "cardinality":
# ES USES DIFFERENT METHOD FOR CARDINALITY
key = canonical_name + " cardinality"
es_query.aggs[key].cardinality.script = s.value.to_painless(
schema).script(schema)
s.pull = jx_expression_to_function(key + ".value")
elif s.aggregate == "stats":
# REGULAR STATS
stats_name = literal_field(canonical_name)
es_query.aggs[
stats_name].extended_stats.script = s.value.to_painless(
schema).script(schema)
# GET MEDIAN TOO!
median_name = literal_field(canonical_name + " percentile")
es_query.aggs[
median_name].percentiles.script = s.value.to_painless(
schema).script(schema)
es_query.aggs[median_name].percentiles.percents += [50]
s.pull = get_pull_stats(stats_name, median_name)
elif s.aggregate == "union":
# USE TERMS AGGREGATE TO SIMULATE union
stats_name = literal_field(canonical_name)
es_query.aggs[stats_name].terms.script_field = s.value.to_painless(
schema).script(schema)
s.pull = jx_expression_to_function(stats_name + ".buckets.key")
else:
# PULL VALUE OUT OF THE stats AGGREGATE
s.pull = jx_expression_to_function(canonical_name + "." +
aggregates[s.aggregate])
es_query.aggs[
canonical_name].extended_stats.script = s.value.to_painless(
schema).script(schema)
decoders = get_decoders_by_depth(query)
start = 0
#<TERRIBLE SECTION> THIS IS WHERE WE WEAVE THE where CLAUSE WITH nested
split_where = split_expression_by_depth(query.where, schema=frum.schema)
if len(split_field(frum.name)) > 1:
if any(split_where[2::]):
Log.error("Where clause is too deep")
for d in decoders[1]:
es_query = d.append_query(es_query, start)
start += d.num_columns
if split_where[1]:
#TODO: INCLUDE FILTERS ON EDGES
filter_ = AndOp("and", split_where[1]).to_esfilter(schema)
es_query = Data(
aggs={"_filter": set_default({"filter": filter_}, es_query)})
es_query = wrap({
"aggs": {
"_nested":
set_default({"nested": {
"path": schema.query_path
}}, es_query)
}
})
else:
if any(split_where[1::]):
Log.error("Where clause is too deep")
if decoders:
for d in jx.reverse(decoders[0]):
es_query = d.append_query(es_query, start)
start += d.num_columns
if split_where[0]:
#TODO: INCLUDE FILTERS ON EDGES
filter = AndOp("and", split_where[0]).to_esfilter(schema)
es_query = Data(
aggs={"_filter": set_default({"filter": filter}, es_query)})
# </TERRIBLE SECTION>
if not es_query:
es_query = wrap({"query": {"match_all": {}}})
es_query.size = 0
with Timer("ES query time") as es_duration:
result = es_post(es, es_query, query.limit)
try:
format_time = Timer("formatting")
with format_time:
decoders = [d for ds in decoders for d in ds]
result.aggregations.doc_count = coalesce(
result.aggregations.doc_count,
result.hits.total) # IT APPEARS THE OLD doc_count IS GONE
formatter, groupby_formatter, aggop_formatter, mime_type = format_dispatch[
query.format]
if query.edges:
output = formatter(decoders, result.aggregations, start, query,
select)
elif query.groupby:
output = groupby_formatter(decoders, result.aggregations,
start, query, select)
else:
output = aggop_formatter(decoders, result.aggregations, start,
query, select)
output.meta.timing.formatting = format_time.duration
output.meta.timing.es_search = es_duration.duration
output.meta.content_type = mime_type
output.meta.es_query = es_query
return output
except Exception as e:
if query.format not in format_dispatch:
Log.error("Format {{format|quote}} not supported yet",
format=query.format,
cause=e)
Log.error("Some problem", cause=e)
def _output():
for g, v in itertools.groupby(data, get_key):
group = Data()
for k, gg in zip(keys, g):
group[k] = gg
yield (group, wrap(list(v)))
def _update_cardinality(self, c):
"""
QUERY ES TO FIND CARDINALITY AND PARTITIONS FOR A SIMPLE COLUMN
"""
if c.type in STRUCT:
Log.error("not supported")
try:
if c.es_index == "meta.columns":
with self.meta.columns.locker:
partitions = jx.sort([
g[c.es_column]
for g, _ in jx.groupby(self.meta.columns, c.es_column)
if g[c.es_column] != None
])
self.meta.columns.update({
"set": {
"partitions": partitions,
"count": len(self.meta.columns),
"cardinality": len(partitions),
"last_updated": Date.now()
},
"where": {
"eq": {
"es_index": c.es_index,
"es_column": c.es_column
}
}
})
return
if c.es_index == "meta.tables":
with self.meta.columns.locker:
partitions = jx.sort([
g[c.es_column]
for g, _ in jx.groupby(self.meta.tables, c.es_column)
if g[c.es_column] != None
])
self.meta.columns.update({
"set": {
"partitions": partitions,
"count": len(self.meta.tables),
"cardinality": len(partitions),
"last_updated": Date.now()
},
"where": {
"eq": {
"es_index": c.es_index,
"es_column": c.es_column
}
}
})
return
es_index = c.es_index.split(".")[0]
result = self.default_es.post("/" + es_index + "/_search",
data={
"aggs": {
c.names["."]:
_counting_query(c)
},
"size": 0
})
r = result.aggregations.values()[0]
count = result.hits.total
cardinality = coalesce(r.value, r._nested.value,
0 if r.doc_count == 0 else None)
if cardinality == None:
Log.error("logic error")
query = Data(size=0)
if cardinality > 1000 or (count >= 30 and cardinality == count
) or (count >= 1000
and cardinality / count > 0.99):
if DEBUG:
Log.note("{{table}}.{{field}} has {{num}} parts",
table=c.es_index,
field=c.es_column,
num=cardinality)
with self.meta.columns.locker:
self.meta.columns.update({
"set": {
"count": count,
"cardinality": cardinality,
"last_updated": Date.now()
},
"clear": ["partitions"],
"where": {
"eq": {
"es_index": c.es_index,
"es_column": c.es_column
}
}
})
return
elif c.type in _elasticsearch.ES_NUMERIC_TYPES and cardinality > 30:
if DEBUG:
Log.note("{{field}} has {{num}} parts",
field=c.name,
num=cardinality)
with self.meta.columns.locker:
self.meta.columns.update({
"set": {
"count": count,
"cardinality": cardinality,
"last_updated": Date.now()
},
"clear": ["partitions"],
"where": {
"eq": {
"es_index": c.es_index,
"es_column": c.es_column
}
}
})
return
elif len(c.nested_path) != 1:
query.aggs[literal_field(c.names["."])] = {
"nested": {
"path": c.nested_path[0]
},
"aggs": {
"_nested": {
"terms": {
"field": c.es_column,
"size": 0
}
}
}
}
else:
query.aggs[literal_field(c.names["."])] = {
"terms": {
"field": c.es_column,
"size": 0
}
}
result = self.default_es.post("/" + es_index + "/_search",
data=query)
aggs = result.aggregations.values()[0]
if aggs._nested:
parts = jx.sort(aggs._nested.buckets.key)
else:
parts = jx.sort(aggs.buckets.key)
if DEBUG:
Log.note("{{field}} has {{parts}}", field=c.name, parts=parts)
with self.meta.columns.locker:
self.meta.columns.update({
"set": {
"count": count,
"cardinality": cardinality,
"partitions": parts,
"last_updated": Date.now()
},
"where": {
"eq": {
"es_index": c.es_index,
"es_column": c.es_column
}
}
})
except Exception as e:
if "IndexMissingException" in e and c.es_index.startswith(
TEST_TABLE_PREFIX):
with self.meta.columns.locker:
self.meta.columns.update({
"set": {
"count": 0,
"cardinality": 0,
"last_updated": Date.now()
},
"clear": ["partitions"],
"where": {
"eq": {
"es_index": c.es_index,
"es_column": c.es_column
}
}
})
else:
self.meta.columns.update({
"set": {
"last_updated": Date.now()
},
"clear": [
"count",
"cardinality",
"partitions",
],
"where": {
"eq": {
"names.\\.": ".",
"es_index": c.es_index,
"es_column": c.es_column
}
}
})
Log.warning(
"Could not get {{col.es_index}}.{{col.es_column}} info",
col=c,
cause=e)
def apply_diff(text, diff, reverse=False, verify=True):
"""
SOME EXAMPLES OF diff
#@@ -1 +1 @@
#-before china goes live, the content team will have to manually update the settings for the china-ready apps currently in marketplace.
#+before china goes live (end January developer release, June general audience release) , the content team will have to manually update the settings for the china-ready apps currently in marketplace.
@@ -0,0 +1,3 @@
+before china goes live, the content team will have to manually update the settings for the china-ready apps currently in marketplace.
+
+kward has the details.
@@ -1 +1 @@
-before china goes live (end January developer release, June general audience release), the content team will have to manually update the settings for the china-ready apps currently in marketplace.
+before china goes live , the content team will have to manually update the settings for the china-ready apps currently in marketplace.
@@ -3 +3 ,6 @@
-kward has the details.+kward has the details.
+
+Target Release Dates :
+https://mana.mozilla.org/wiki/display/PM/Firefox+OS+Wave+Launch+Cross+Functional+View
+
+Content Team Engagement & Tasks : https://appreview.etherpad.mozilla.org/40
"""
if not diff:
return text
output = text
hunks = [
(new_diff[start_hunk], new_diff[start_hunk + 1:end_hunk])
for new_diff in [[
d.lstrip()
for d in diff if d.lstrip() and d != "\\ No newline at end of file"
] + ["@@"]] # ANOTHER REPAIR
for start_hunk, end_hunk in pairwise(
i for i, l in enumerate(new_diff) if l.startswith('@@'))
]
for header, hunk_body in (reversed(hunks) if reverse else hunks):
matches = DIFF_PREFIX.match(header.strip())
if not matches:
if not _Log:
_late_import()
_Log.error("Can not handle \n---\n{{diff}}\n---\n", diff=diff)
removes = tuple(int(i.strip()) for i in matches.group(1).split(
",")) # EXPECTING start_line, length TO REMOVE
remove = Data(
start=removes[0],
length=1 if len(removes) == 1 else removes[1]) # ASSUME FIRST LINE
adds = tuple(int(i.strip()) for i in matches.group(2).split(
",")) # EXPECTING start_line, length TO ADD
add = Data(start=adds[0], length=1 if len(adds) == 1 else adds[1])
if add.length == 0 and add.start == 0:
add.start = remove.start
def repair_hunk(hunk_body):
# THE LAST DELETED LINE MAY MISS A "\n" MEANING THE FIRST
# ADDED LINE WILL BE APPENDED TO THE LAST DELETED LINE
# EXAMPLE: -kward has the details.+kward has the details.
# DETECT THIS PROBLEM FOR THIS HUNK AND FIX THE DIFF
if reverse:
last_lines = [
o for b, o in zip(reversed(hunk_body), reversed(output))
if b != "+" + o
]
if not last_lines:
return hunk_body
last_line = last_lines[0]
for problem_index, problem_line in enumerate(hunk_body):
if problem_line.startswith('-') and problem_line.endswith(
'+' + last_line):
split_point = len(problem_line) - (len(last_line) + 1)
break
elif problem_line.startswith('+' + last_line + "-"):
split_point = len(last_line) + 1
break
else:
return hunk_body
else:
if not output:
return hunk_body
last_line = output[-1]
for problem_index, problem_line in enumerate(hunk_body):
if problem_line.startswith('+') and problem_line.endswith(
'-' + last_line):
split_point = len(problem_line) - (len(last_line) + 1)
break
elif problem_line.startswith('-' + last_line + "+"):
split_point = len(last_line) + 1
break
else:
return hunk_body
new_hunk_body = (
hunk_body[:problem_index] +
[problem_line[:split_point], problem_line[split_point:]] +
hunk_body[problem_index + 1:])
return new_hunk_body
hunk_body = repair_hunk(hunk_body)
if reverse:
new_output = (output[:add.start - 1] +
[d[1:] for d in hunk_body if d and d[0] == '-'] +
output[add.start + add.length - 1:])
else:
new_output = (output[:add.start - 1] +
[d[1:] for d in hunk_body if d and d[0] == '+'] +
output[add.start + remove.length - 1:])
output = new_output
if verify:
original = apply_diff(output, diff, not reverse, False)
if set(text) != set(original): # bugzilla-etl diffs are a jumble
for t, o in zip_longest(text, original):
if t in ['reports: https://goo.gl/70o6w6\r']:
break # KNOWN INCONSISTENCIES
if t != o:
if not _Log:
_late_import()
_Log.error("logical verification check failed")
break
return output
def __getitem__(self, item):
if item == "from":
return self.frum
return Data.__getitem__(self, item)
def _set_op(self, query, frum):
# GET LIST OF COLUMNS
frum_path = split_field(frum)
primary_nested_path = join_field(frum_path[1:])
vars_ = UNION([s.value.vars() for s in listwrap(query.select)])
schema = self.sf.tables[primary_nested_path].schema
nest_to_alias = {
nested_path: "__" + unichr(ord('a') + i) + "__"
for i, (nested_path, sub_table) in enumerate(self.sf.tables.items())
}
active_columns = {".": []}
for cname, cols in schema.items():
if any(startswith_field(cname, v) for v in vars_):
for c in cols:
if c.type in STRUCT:
continue
nest = c.nested_path[0]
active = active_columns.get(nest)
if not active:
active = active_columns[nest] = []
active.append(c)
for nested_path, s in self.sf.tables.items():
for cname, cols in s.schema.items():
if not any(startswith_field(cname, c.names[c.nested_path[0]]) for n, cc in active_columns.items() for c in cc):
for c in cols:
if c.type in STRUCT:
continue
nest = c.nested_path[0]
active = active_columns.get(nest)
if not active:
active = active_columns[nest] = []
active.append(c)
# ANY VARS MENTIONED WITH NO COLUMNS?
for v in vars_:
if not any(startswith_field(cname, v) for cname in schema.keys()):
active_columns["."].append(Column(
names={".": v},
type="null",
es_column=".",
es_index=".",
nested_path=["."]
))
# EVERY COLUMN, AND THE INDEX IT TAKES UP
index_to_column = {} # MAP FROM INDEX TO COLUMN (OR SELECT CLAUSE)
index_to_uid = {} # FROM NESTED PATH TO THE INDEX OF UID
sql_selects = [] # EVERY SELECT CLAUSE (NOT TO BE USED ON ALL TABLES, OF COURSE)
nest_to_alias = {
nested_path: "__" + unichr(ord('a') + i) + "__"
for i, (nested_path, sub_table) in enumerate(self.sf.tables.items())
}
sorts = []
if query.sort:
for s in query.sort:
col = s.value.to_sql(schema)[0]
for t, sql in col.sql.items():
json_type = sql_type_to_json_type[t]
if json_type in STRUCT:
continue
column_number = len(sql_selects)
# SQL HAS ABS TABLE REFERENCE
column_alias = _make_column_name(column_number)
sql_selects.append(sql + " AS " + column_alias)
if s.sort == -1:
sorts.append(column_alias + " IS NOT NULL")
sorts.append(column_alias + " DESC")
else:
sorts.append(column_alias + " IS NULL")
sorts.append(column_alias)
selects = []
primary_doc_details = Data()
# EVERY SELECT STATEMENT THAT WILL BE REQUIRED, NO MATTER THE DEPTH
# WE WILL CREATE THEM ACCORDING TO THE DEPTH REQUIRED
for nested_path, sub_table in self.sf.tables.items():
nested_doc_details = {
"sub_table": sub_table,
"children": [],
"index_to_column": {},
"nested_path": [nested_path] # fake the real nested path, we only look at [0] anyway
}
# INSERT INTO TREE
if not primary_doc_details:
primary_doc_details = nested_doc_details
else:
def place(parent_doc_details):
if startswith_field(nested_path, parent_doc_details['nested_path'][0]):
for c in parent_doc_details['children']:
if place(c):
return True
parent_doc_details['children'].append(nested_doc_details)
place(primary_doc_details)
alias = nested_doc_details['alias'] = nest_to_alias[nested_path]
if nested_path=="." and quoted_GUID in vars_:
column_number = index_to_uid[nested_path] = nested_doc_details['id_coord'] = len(sql_selects)
sql_select = alias + "." + quoted_GUID
sql_selects.append(sql_select + " AS " + _make_column_name(column_number))
index_to_column[column_number] = nested_doc_details['index_to_column'][column_number] = ColumnMapping(
push_name="_id",
push_column_name="_id",
push_column=0,
push_child=".",
sql=sql_select,
pull=get_column(column_number),
type="string",
column_alias=_make_column_name(column_number),
nested_path=[nested_path] # fake the real nested path, we only look at [0] anyway
)
query.select = [s for s in listwrap(query.select) if s.name!="_id"]
# WE ALWAYS ADD THE UID AND ORDER
column_number = index_to_uid[nested_path] = nested_doc_details['id_coord'] = len(sql_selects)
sql_select = alias + "." + quoted_UID
sql_selects.append(sql_select + " AS " + _make_column_name(column_number))
if nested_path !=".":
index_to_column[column_number]=ColumnMapping(
sql=sql_select,
type="number",
nested_path=[nested_path], # fake the real nested path, we only look at [0] anyway
column_alias=_make_column_name(column_number)
)
column_number = len(sql_selects)
sql_select = alias + "." + quote_table(ORDER)
sql_selects.append(sql_select + " AS " + _make_column_name(column_number))
index_to_column[column_number]=ColumnMapping(
sql=sql_select,
type="number",
nested_path=[nested_path], # fake the real nested path, we only look at [0] anyway
column_alias=_make_column_name(column_number)
)
# WE DO NOT NEED DATA FROM TABLES WE REQUEST NOTHING FROM
if nested_path not in active_columns:
continue
if len(active_columns[nested_path]) != 0:
# ADD SQL SELECT COLUMNS FOR EACH jx SELECT CLAUSE
si = 0
for s in listwrap(query.select):
try:
column_number = len(sql_selects)
s.pull = get_column(column_number)
db_columns = s.value.to_sql(schema)
if isinstance(s.value, LeavesOp):
for column in db_columns:
if isinstance(column.nested_path, list):
column.nested_path=column.nested_path[0]
if column.nested_path and column.nested_path!=nested_path:
continue
for t, unsorted_sql in column.sql.items():
json_type = sql_type_to_json_type[t]
if json_type in STRUCT:
continue
column_number = len(sql_selects)
# SQL HAS ABS TABLE REFERENCE
column_alias = _make_column_name(column_number)
if concat_field(alias, unsorted_sql) in selects and len(unsorted_sql.split())==1:
continue
selects.append(concat_field(alias, unsorted_sql))
sql_selects.append(alias + "." + unsorted_sql + " AS " + column_alias)
index_to_column[column_number] = nested_doc_details['index_to_column'][column_number] = ColumnMapping(
push_name=literal_field(get_property_name(concat_field(s.name, column.name))),
push_column_name=get_property_name(concat_field(s.name, column.name)),
push_column=si,
push_child=".",
pull=get_column(column_number),
sql=unsorted_sql,
type=json_type,
column_alias=column_alias,
nested_path=[nested_path] # fake the real nested path, we only look at [0] anyway
)
si += 1
else:
for column in db_columns:
if isinstance(column.nested_path, list):
column.nested_path=column.nested_path[0]
if column.nested_path and column.nested_path!=nested_path:
continue
for t, unsorted_sql in column.sql.items():
json_type = sql_type_to_json_type[t]
if json_type in STRUCT:
continue
column_number = len(sql_selects)
# SQL HAS ABS TABLE REFERENCE
column_alias = _make_column_name(column_number)
if concat_field(alias, unsorted_sql) in selects and len(unsorted_sql.split())==1:
continue
selects.append(concat_field(alias, unsorted_sql))
sql_selects.append(alias + "." + unsorted_sql + " AS " + column_alias)
index_to_column[column_number] = nested_doc_details['index_to_column'][column_number] = ColumnMapping(
push_name=s.name,
push_column_name=s.name,
push_column=si,
push_child=column.name,
pull=get_column(column_number),
sql=unsorted_sql,
type=json_type,
column_alias=column_alias,
nested_path=[nested_path]
# fake the real nested path, we only look at [0] anyway
)
finally:
si += 1
elif startswith_field(nested_path, primary_nested_path):
# ADD REQUIRED COLUMNS, FOR DEEP STUFF
for ci, c in enumerate(active_columns[nested_path]):
if c.type in STRUCT:
continue
column_number = len(sql_selects)
nested_path = c.nested_path
unsorted_sql = nest_to_alias[nested_path[0]] + "." + quote_table(c.es_column)
column_alias = _make_column_name(column_number)
if concat_field(alias, unsorted_sql) in selects and len(unsorted_sql.split())==1:
continue
selects.append(concat_field(alias, unsorted_sql))
sql_selects.append(alias + "." + unsorted_sql + " AS " + column_alias)
index_to_column[column_number] = nested_doc_details['index_to_column'][column_number] = ColumnMapping(
push_name=s.name,
push_column_name=s.name,
push_column=si,
push_child=relative_field(c.names["."], s.name),
pull=get_column(column_number),
sql=unsorted_sql,
type=c.type,
column_alias=column_alias,
nested_path=nested_path
)
where_clause = query.where.to_sql(schema, boolean=True)[0].sql.b
unsorted_sql = self._make_sql_for_one_nest_in_set_op(
".",
sql_selects,
where_clause,
active_columns,
index_to_column
)
for n, _ in self.sf.tables.items():
sorts.append(COLUMN + text_type(index_to_uid[n]))
ordered_sql = (
"SELECT * FROM (\n" +
unsorted_sql +
"\n)" +
"\nORDER BY\n" + ",\n".join(sorts) +
"\nLIMIT " + quote_value(query.limit)
)
self.db.create_new_functions() #creating new functions: regexp
result = self.db.query(ordered_sql)
def _accumulate_nested(rows, row, nested_doc_details, parent_doc_id, parent_id_coord):
"""
:param rows: REVERSED STACK OF ROWS (WITH push() AND pop())
:param row: CURRENT ROW BEING EXTRACTED
:param nested_doc_details: {
"nested_path": wrap_nested_path(nested_path),
"index_to_column": map from column number to column details
"children": all possible direct decedents' nested_doc_details
}
:param parent_doc_id: the id of the parent doc (for detecting when to step out of loop)
:param parent_id_coord: the column number for the parent id (so we ca extract from each row)
:return: the nested property (usually an array)
"""
previous_doc_id = None
doc = Null
output = []
id_coord = nested_doc_details['id_coord']
while True:
doc_id = row[id_coord]
if doc_id == None or (parent_id_coord is not None and row[parent_id_coord] != parent_doc_id):
rows.append(row) # UNDO PREVIOUS POP (RECORD IS NOT A NESTED RECORD OF parent_doc)
return output
if doc_id != previous_doc_id:
previous_doc_id = doc_id
doc = Null
curr_nested_path = nested_doc_details['nested_path'][0]
index_to_column = nested_doc_details['index_to_column'].items()
if index_to_column:
for i, c in index_to_column:
value = row[i]
if value == None:
continue
if value == '':
continue
if isinstance(query.select, list) or isinstance(query.select.value, LeavesOp):
# ASSIGN INNER PROPERTIES
relative_path=join_field([c.push_name]+split_field(c.push_child))
else: # FACT IS EXPECTED TO BE A SINGLE VALUE, NOT AN OBJECT
relative_path=c.push_child
if relative_path == ".":
doc = value
elif doc is Null:
doc = Data()
doc[relative_path] = value
else:
doc[relative_path] = value
for child_details in nested_doc_details['children']:
# EACH NESTED TABLE MUST BE ASSEMBLED INTO A LIST OF OBJECTS
child_id = row[child_details['id_coord']]
if child_id is not None:
nested_value = _accumulate_nested(rows, row, child_details, doc_id, id_coord)
if nested_value:
push_name = child_details['nested_path'][0]
if isinstance(query.select, list) or isinstance(query.select.value, LeavesOp):
# ASSIGN INNER PROPERTIES
relative_path=relative_field(push_name, curr_nested_path)
else: # FACT IS EXPECTED TO BE A SINGLE VALUE, NOT AN OBJECT
relative_path="."
if relative_path == "." and doc is Null:
doc = nested_value
elif relative_path == ".":
doc[push_name] = unwraplist([v[push_name] for v in nested_value])
elif doc is Null:
doc = Data()
doc[relative_path] = unwraplist(nested_value)
else:
doc[relative_path] = unwraplist(nested_value)
output.append(doc)
try:
row = rows.pop()
except IndexError:
return output
cols = tuple([i for i in index_to_column.values() if i.push_name != None])
rows = list(reversed(unwrap(result.data)))
if rows:
row = rows.pop()
data = _accumulate_nested(rows, row, primary_doc_details, None, None)
else:
data = result.data
if query.format == "cube":
for f, _ in self.sf.tables.items():
if frum.endswith(f) or (test_dots(cols) and isinstance(query.select, list)):
num_rows = len(result.data)
num_cols = MAX([c.push_column for c in cols]) + 1 if len(cols) else 0
map_index_to_name = {c.push_column: c.push_column_name for c in cols}
temp_data = [[None]*num_rows for _ in range(num_cols)]
for rownum, d in enumerate(result.data):
for c in cols:
if c.push_child == ".":
temp_data[c.push_column][rownum] = c.pull(d)
else:
column = temp_data[c.push_column][rownum]
if column is None:
column = temp_data[c.push_column][rownum] = Data()
column[c.push_child] = c.pull(d)
output = Data(
meta={"format": "cube"},
data={n: temp_data[c] for c, n in map_index_to_name.items()},
edges=[{
"name": "rownum",
"domain": {
"type": "rownum",
"min": 0,
"max": num_rows,
"interval": 1
}
}]
)
return output
if isinstance(query.select, list) or isinstance(query.select.value, LeavesOp):
num_rows = len(data)
map_index_to_name = {c.push_column: c.push_column_name for c in cols}
temp_data = Data()
for rownum, d in enumerate(data):
for k, v in d.items():
if temp_data[k] == None:
temp_data[k] = [None] * num_rows
temp_data[k][rownum] = v
return Data(
meta={"format": "cube"},
data={n: temp_data[literal_field(n)] for c, n in map_index_to_name.items()},
edges=[{
"name": "rownum",
"domain": {
"type": "rownum",
"min": 0,
"max": num_rows,
"interval": 1
}
}]
)
else:
num_rows = len(data)
map_index_to_name = {c.push_column: c.push_column_name for c in cols}
temp_data = [data]
return Data(
meta={"format": "cube"},
data={n: temp_data[c] for c, n in map_index_to_name.items()},
edges=[{
"name": "rownum",
"domain": {
"type": "rownum",
"min": 0,
"max": num_rows,
"interval": 1
}
}]
)
elif query.format == "table":
for f, _ in self.sf.tables.items():
if frum.endswith(f):
num_column = MAX([c.push_column for c in cols])+1
header = [None]*num_column
for c in cols:
header[c.push_column] = c.push_column_name
output_data = []
for d in result.data:
row = [None] * num_column
for c in cols:
set_column(row, c.push_column, c.push_child, c.pull(d))
output_data.append(row)
return Data(
meta={"format": "table"},
header=header,
data=output_data
)
if isinstance(query.select, list) or isinstance(query.select.value, LeavesOp):
num_rows = len(data)
column_names= [None]*(max(c.push_column for c in cols) + 1)
for c in cols:
column_names[c.push_column] = c.push_column_name
temp_data = []
for rownum, d in enumerate(data):
row =[None] * len(column_names)
for i, (k, v) in enumerate(sorted(d.items())):
for c in cols:
if k==c.push_name:
row[c.push_column] = v
temp_data.append(row)
return Data(
meta={"format": "table"},
header=column_names,
data=temp_data
)
else:
column_names = listwrap(query.select).name
return Data(
meta={"format": "table"},
header=column_names,
data=[[d] for d in data]
)
else:
for f, _ in self.sf.tables.items():
if frum.endswith(f) or (test_dots(cols) and isinstance(query.select, list)):
data = []
for d in result.data:
row = Data()
for c in cols:
if c.push_child == ".":
row[c.push_name] = c.pull(d)
elif c.num_push_columns:
tuple_value = row[c.push_name]
if not tuple_value:
tuple_value = row[c.push_name] = [None] * c.num_push_columns
tuple_value[c.push_child] = c.pull(d)
elif not isinstance(query.select, list): # select is value type
row[c.push_child]=c.pull(d)
else:
row[c.push_name][c.push_child] = c.pull(d)
data.append(row)
return Data(
meta={"format": "list"},
data=data
)
if isinstance(query.select, list) or isinstance(query.select.value, LeavesOp):
temp_data=[]
for rownum, d in enumerate(data):
row = {}
for k, v in d.items():
for c in cols:
if c.push_name==c.push_column_name==k:
row[c.push_column_name] = v
elif c.push_name==k and c.push_column_name!=k:
row[c.push_column_name] = v
temp_data.append(row)
return Data(
meta={"format": "list"},
data=temp_data
)
else:
return Data(
meta={"format": "list"},
data=data
)
def apply_diff(text, diff, reverse=False, verify=True):
"""
SOME EXAMPLES OF diff
#@@ -1 +1 @@
#-before china goes live, the content team will have to manually update the settings for the china-ready apps currently in marketplace.
#+before china goes live (end January developer release, June general audience release) , the content team will have to manually update the settings for the china-ready apps currently in marketplace.
@@ -0,0 +1,3 @@
+before china goes live, the content team will have to manually update the settings for the china-ready apps currently in marketplace.
+
+kward has the details.
@@ -1 +1 @@
-before china goes live (end January developer release, June general audience release), the content team will have to manually update the settings for the china-ready apps currently in marketplace.
+before china goes live , the content team will have to manually update the settings for the china-ready apps currently in marketplace.
@@ -3 +3 ,6 @@
-kward has the details.+kward has the details.
+
+Target Release Dates :
+https://mana.mozilla.org/wiki/display/PM/Firefox+OS+Wave+Launch+Cross+Functional+View
+
+Content Team Engagement & Tasks : https://appreview.etherpad.mozilla.org/40
"""
if not diff:
return text
output = text
hunks = [
(new_diff[start_hunk], new_diff[start_hunk+1:end_hunk])
for new_diff in [[d.lstrip() for d in diff if d.lstrip() and d != "\\ No newline at end of file"] + ["@@"]] # ANOTHER REPAIR
for start_hunk, end_hunk in pairwise(i for i, l in enumerate(new_diff) if l.startswith('@@'))
]
for header, hunk_body in (reversed(hunks) if reverse else hunks):
matches = DIFF_PREFIX.match(header.strip())
if not matches:
if not _Log:
_late_import()
_Log.error("Can not handle \n---\n{{diff}}\n---\n", diff=diff)
removes = tuple(int(i.strip()) for i in matches.group(1).split(",")) # EXPECTING start_line, length TO REMOVE
remove = Data(start=removes[0], length=1 if len(removes) == 1 else removes[1]) # ASSUME FIRST LINE
adds = tuple(int(i.strip()) for i in matches.group(2).split(",")) # EXPECTING start_line, length TO ADD
add = Data(start=adds[0], length=1 if len(adds) == 1 else adds[1])
if add.length == 0 and add.start == 0:
add.start = remove.start
def repair_hunk(hunk_body):
# THE LAST DELETED LINE MAY MISS A "\n" MEANING THE FIRST
# ADDED LINE WILL BE APPENDED TO THE LAST DELETED LINE
# EXAMPLE: -kward has the details.+kward has the details.
# DETECT THIS PROBLEM FOR THIS HUNK AND FIX THE DIFF
if reverse:
last_lines = [
o
for b, o in zip(reversed(hunk_body), reversed(output))
if b != "+" + o
]
if not last_lines:
return hunk_body
last_line = last_lines[0]
for problem_index, problem_line in enumerate(hunk_body):
if problem_line.startswith('-') and problem_line.endswith('+' + last_line):
split_point = len(problem_line) - (len(last_line) + 1)
break
elif problem_line.startswith('+' + last_line + "-"):
split_point = len(last_line) + 1
break
else:
return hunk_body
else:
if not output:
return hunk_body
last_line = output[-1]
for problem_index, problem_line in enumerate(hunk_body):
if problem_line.startswith('+') and problem_line.endswith('-' + last_line):
split_point = len(problem_line) - (len(last_line) + 1)
break
elif problem_line.startswith('-' + last_line + "+"):
split_point = len(last_line) + 1
break
else:
return hunk_body
new_hunk_body = (
hunk_body[:problem_index] +
[problem_line[:split_point], problem_line[split_point:]] +
hunk_body[problem_index + 1:]
)
return new_hunk_body
hunk_body = repair_hunk(hunk_body)
if reverse:
new_output = (
output[:add.start - 1] +
[d[1:] for d in hunk_body if d and d[0] == '-'] +
output[add.start + add.length - 1:]
)
else:
new_output = (
output[:add.start - 1] +
[d[1:] for d in hunk_body if d and d[0] == '+'] +
output[add.start + remove.length - 1:]
)
output = new_output
if verify:
original = apply_diff(output, diff, not reverse, False)
if set(text) != set(original): # bugzilla-etl diffs are a jumble
for t, o in zip_longest(text, original):
if t in ['reports: https://goo.gl/70o6w6\r']:
break # KNOWN INCONSISTENCIES
if t != o:
if not _Log:
_late_import()
_Log.error("logical verification check failed")
break
return output
def _accumulate_nested(rows, row, nested_doc_details, parent_doc_id, parent_id_coord):
"""
:param rows: REVERSED STACK OF ROWS (WITH push() AND pop())
:param row: CURRENT ROW BEING EXTRACTED
:param nested_doc_details: {
"nested_path": wrap_nested_path(nested_path),
"index_to_column": map from column number to column details
"children": all possible direct decedents' nested_doc_details
}
:param parent_doc_id: the id of the parent doc (for detecting when to step out of loop)
:param parent_id_coord: the column number for the parent id (so we ca extract from each row)
:return: the nested property (usually an array)
"""
previous_doc_id = None
doc = Null
output = []
id_coord = nested_doc_details['id_coord']
while True:
doc_id = row[id_coord]
if doc_id == None or (parent_id_coord is not None and row[parent_id_coord] != parent_doc_id):
rows.append(row) # UNDO PREVIOUS POP (RECORD IS NOT A NESTED RECORD OF parent_doc)
return output
if doc_id != previous_doc_id:
previous_doc_id = doc_id
doc = Null
curr_nested_path = nested_doc_details['nested_path'][0]
index_to_column = nested_doc_details['index_to_column'].items()
if index_to_column:
for i, c in index_to_column:
value = row[i]
if value == None:
continue
if value == '':
continue
if isinstance(query.select, list) or isinstance(query.select.value, LeavesOp):
# ASSIGN INNER PROPERTIES
relative_path=join_field([c.push_name]+split_field(c.push_child))
else: # FACT IS EXPECTED TO BE A SINGLE VALUE, NOT AN OBJECT
relative_path=c.push_child
if relative_path == ".":
doc = value
elif doc is Null:
doc = Data()
doc[relative_path] = value
else:
doc[relative_path] = value
for child_details in nested_doc_details['children']:
# EACH NESTED TABLE MUST BE ASSEMBLED INTO A LIST OF OBJECTS
child_id = row[child_details['id_coord']]
if child_id is not None:
nested_value = _accumulate_nested(rows, row, child_details, doc_id, id_coord)
if nested_value:
push_name = child_details['nested_path'][0]
if isinstance(query.select, list) or isinstance(query.select.value, LeavesOp):
# ASSIGN INNER PROPERTIES
relative_path=relative_field(push_name, curr_nested_path)
else: # FACT IS EXPECTED TO BE A SINGLE VALUE, NOT AN OBJECT
relative_path="."
if relative_path == "." and doc is Null:
doc = nested_value
elif relative_path == ".":
doc[push_name] = unwraplist([v[push_name] for v in nested_value])
elif doc is Null:
doc = Data()
doc[relative_path] = unwraplist(nested_value)
else:
doc[relative_path] = unwraplist(nested_value)
output.append(doc)
try:
row = rows.pop()
except IndexError:
return output
def _get_single_branch_from_hg(settings, description, dir):
if dir == "users":
return []
response = http.get(settings.url + "/" + dir)
doc = BeautifulSoup(response.all_content, "html.parser")
output = []
try:
all_branches = doc("table")[0]
except Exception:
return []
for i, b in enumerate(all_branches("tr")):
if i == 0:
continue # IGNORE HEADER
columns = b("td")
try:
path = columns[0].a.get('href')
if path == "/":
continue
name, desc, last_used = [c.text.strip() for c in columns][0:3]
if last_used.startswith('at'):
last_used = last_used[2:]
detail = Data(
name=name.lower(),
locale=DEFAULT_LOCALE,
parent_name=description,
url=settings.url + path,
description=desc,
last_used=Date(last_used),
etl={"timestamp": Date.now()}
)
if detail.description == "unknown":
detail.description = None
# SOME BRANCHES HAVE NAME COLLISIONS, IGNORE LEAST POPULAR
if path in [
"/projects/dxr/", # moved to webtools
"/build/compare-locales/", # ?build team likes to clone?
"/build/puppet/", # ?build team likes to clone?
"/SeaMonkey/puppet/", # looses the popularity contest
"/releases/gaia-l10n/v1_2/en-US/", # use default branch
"/releases/gaia-l10n/v1_3/en-US/", # use default branch
"/releases/gaia-l10n/v1_4/en-US/", # use default branch
"/releases/gaia-l10n/v2_0/en-US/", # use default branch
"/releases/gaia-l10n/v2_1/en-US/", # use default branch
"/build/autoland/"
]:
continue
# MARKUP BRANCH IF LOCALE SPECIFIC
if path.startswith("/l10n-central"):
_path = path.strip("/").split("/")
detail.locale = _path[-1]
detail.name = "mozilla-central"
elif path.startswith("/releases/l10n/"):
_path = path.strip("/").split("/")
detail.locale = _path[-1]
detail.name = _path[-2].lower()
elif path.startswith("/releases/gaia-l10n/"):
_path = path.strip("/").split("/")
detail.locale = _path[-1]
detail.name = "gaia-" + _path[-2][1::]
elif path.startswith("/weave-l10n"):
_path = path.strip("/").split("/")
detail.locale = _path[-1]
detail.name = "weave"
if BRANCH_WHITELIST is not None:
found = False
for br in BRANCH_WHITELIST:
if br in str(detail.name):
found = True
break
if not found:
continue
Log.note("Branch {{name}} {{locale}}", name=detail.name, locale=detail.locale)
output.append(detail)
except Exception as e:
Log.warning("branch digestion problem", cause=e)
return output
def __new__(cls, e=None, query=None, *args, **kwargs):
e.allowNulls = coalesce(e.allowNulls, True)
if e.value and e.domain.type == "default":
# if query.groupby:
# return object.__new__(DefaultDecoder, e)
if isinstance(e.value, (text_type, binary_type)):
Log.error("Expecting Variable or Expression, not plain string")
if isinstance(e.value, LeavesOp):
return object.__new__(ObjectDecoder, e)
elif isinstance(e.value, TupleOp):
# THIS domain IS FROM A dimension THAT IS A SIMPLE LIST OF fields
# JUST PULL THE FIELDS
if not all(isinstance(t, Variable) for t in e.value.terms):
Log.error("Can only handle variables in tuples")
e.domain = Data(dimension={"fields": e.value.terms})
return object.__new__(DimFieldListDecoder, e)
elif isinstance(e.value, Variable):
schema = query.frum.schema
cols = schema.leaves(e.value.var)
if not cols:
return object.__new__(DefaultDecoder, e)
if len(cols) != 1:
return object.__new__(ObjectDecoder, e)
col = cols[0]
limit = coalesce(e.domain.limit, query.limit, DEFAULT_LIMIT)
if col.partitions != None:
if col.multi > 1 and len(col.partitions) < 6:
return object.__new__(MultivalueDecoder)
partitions = col.partitions[:limit:]
if e.domain.sort == -1:
partitions = list(reversed(sorted(partitions)))
else:
partitions = sorted(partitions)
e.domain = SimpleSetDomain(partitions=partitions,
limit=limit)
else:
e.domain = set_default(DefaultDomain(limit=limit),
e.domain.__data__())
return object.__new__(DefaultDecoder, e)
else:
return object.__new__(DefaultDecoder, e)
if e.value and e.domain.type in PARTITION:
return object.__new__(SetDecoder, e)
if isinstance(e.domain.dimension, Dimension):
e.domain = e.domain.dimension.getDomain()
return object.__new__(SetDecoder, e)
if e.value and e.domain.type == "time":
return object.__new__(TimeDecoder, e)
if e.range:
return object.__new__(GeneralRangeDecoder, e)
if e.value and e.domain.type == "duration":
return object.__new__(DurationDecoder, e)
elif e.value and e.domain.type == "range":
return object.__new__(RangeDecoder, e)
elif not e.value and e.domain.dimension.fields:
# THIS domain IS FROM A dimension THAT IS A SIMPLE LIST OF fields
# JUST PULL THE FIELDS
fields = e.domain.dimension.fields
if isinstance(fields, Mapping):
Log.error("No longer allowed: All objects are expressions")
else:
return object.__new__(DimFieldListDecoder, e)
elif not e.value and all(e.domain.partitions.where):
return object.__new__(GeneralSetDecoder, e)
else:
Log.error("domain type of {{type}} is not supported yet",
type=e.domain.type)
def selector(d):
output = Data()
for n, p in push_and_pull:
output[n] = unwraplist(p(wrap(d)))
return unwrap(output)
def es_aggsop(es, frum, query):
select = wrap([s.copy() for s in listwrap(query.select)])
# [0] is a cheat; each es_column should be a dict of columns keyed on type, like in sqlite
es_column_map = {v: frum.schema[v][0].es_column for v in query.vars()}
es_query = Data()
new_select = Data() #MAP FROM canonical_name (USED FOR NAMES IN QUERY) TO SELECT MAPPING
formula = []
for s in select:
if s.aggregate == "count" and isinstance(s.value, Variable) and s.value.var == ".":
s.pull = "doc_count"
elif isinstance(s.value, Variable):
if s.value.var == ".":
if frum.typed:
# STATISITCAL AGGS IMPLY $value, WHILE OTHERS CAN BE ANYTHING
if s.aggregate in NON_STATISTICAL_AGGS:
#TODO: HANDLE BOTH $value AND $objects TO COUNT
Log.error("do not know how to handle")
else:
s.value.var = "$value"
new_select["$value"] += [s]
else:
if s.aggregate in NON_STATISTICAL_AGGS:
#TODO: WE SHOULD BE ABLE TO COUNT, BUT WE MUST *OR* ALL LEAF VALUES TO DO IT
Log.error("do not know how to handle")
else:
Log.error('Not expecting ES to have a value at "." which {{agg}} can be applied', agg=s.aggregate)
elif s.aggregate == "count":
s.value = s.value.map(es_column_map)
new_select["count_"+literal_field(s.value.var)] += [s]
else:
s.value = s.value.map(es_column_map)
new_select[literal_field(s.value.var)] += [s]
else:
formula.append(s)
for canonical_name, many in new_select.items():
representative = many[0]
if representative.value.var == ".":
Log.error("do not know how to handle")
else:
field_name = representative.value.var
# canonical_name=literal_field(many[0].name)
for s in many:
if s.aggregate == "count":
es_query.aggs[literal_field(canonical_name)].value_count.field = field_name
s.pull = literal_field(canonical_name) + ".value"
elif s.aggregate == "median":
# ES USES DIFFERENT METHOD FOR PERCENTILES
key = literal_field(canonical_name + " percentile")
es_query.aggs[key].percentiles.field = field_name
es_query.aggs[key].percentiles.percents += [50]
s.pull = key + ".values.50\.0"
elif s.aggregate == "percentile":
# ES USES DIFFERENT METHOD FOR PERCENTILES
key = literal_field(canonical_name + " percentile")
if isinstance(s.percentile, basestring) or s.percetile < 0 or 1 < s.percentile:
Log.error("Expecting percentile to be a float from 0.0 to 1.0")
percent = Math.round(s.percentile * 100, decimal=6)
es_query.aggs[key].percentiles.field = field_name
es_query.aggs[key].percentiles.percents += [percent]
s.pull = key + ".values." + literal_field(unicode(percent))
elif s.aggregate == "cardinality":
# ES USES DIFFERENT METHOD FOR CARDINALITY
key = literal_field(canonical_name + " cardinality")
es_query.aggs[key].cardinality.field = field_name
s.pull = key + ".value"
elif s.aggregate == "stats":
# REGULAR STATS
stats_name = literal_field(canonical_name)
es_query.aggs[stats_name].extended_stats.field = field_name
# GET MEDIAN TOO!
median_name = literal_field(canonical_name + " percentile")
es_query.aggs[median_name].percentiles.field = field_name
es_query.aggs[median_name].percentiles.percents += [50]
s.pull = {
"count": stats_name + ".count",
"sum": stats_name + ".sum",
"min": stats_name + ".min",
"max": stats_name + ".max",
"avg": stats_name + ".avg",
"sos": stats_name + ".sum_of_squares",
"std": stats_name + ".std_deviation",
"var": stats_name + ".variance",
"median": median_name + ".values.50\.0"
}
elif s.aggregate == "union":
# USE TERMS AGGREGATE TO SIMULATE union
stats_name = literal_field(canonical_name)
es_query.aggs[stats_name].terms.field = field_name
es_query.aggs[stats_name].terms.size = Math.min(s.limit, MAX_LIMIT)
s.pull = stats_name + ".buckets.key"
else:
# PULL VALUE OUT OF THE stats AGGREGATE
es_query.aggs[literal_field(canonical_name)].extended_stats.field = field_name
s.pull = literal_field(canonical_name) + "." + aggregates1_4[s.aggregate]
for i, s in enumerate(formula):
canonical_name = literal_field(s.name)
abs_value = s.value.map(es_column_map)
if isinstance(abs_value, TupleOp):
if s.aggregate == "count":
# TUPLES ALWAYS EXIST, SO COUNTING THEM IS EASY
s.pull = "doc_count"
else:
Log.error("{{agg}} is not a supported aggregate over a tuple", agg=s.aggregate)
elif s.aggregate == "count":
es_query.aggs[literal_field(canonical_name)].value_count.script = abs_value.to_ruby()
s.pull = literal_field(canonical_name) + ".value"
elif s.aggregate == "median":
# ES USES DIFFERENT METHOD FOR PERCENTILES THAN FOR STATS AND COUNT
key = literal_field(canonical_name + " percentile")
es_query.aggs[key].percentiles.script = abs_value.to_ruby()
es_query.aggs[key].percentiles.percents += [50]
s.pull = key + ".values.50\.0"
elif s.aggregate == "percentile":
# ES USES DIFFERENT METHOD FOR PERCENTILES THAN FOR STATS AND COUNT
key = literal_field(canonical_name + " percentile")
percent = Math.round(s.percentile * 100, decimal=6)
es_query.aggs[key].percentiles.script = abs_value.to_ruby()
es_query.aggs[key].percentiles.percents += [percent]
s.pull = key + ".values." + literal_field(unicode(percent))
elif s.aggregate == "cardinality":
# ES USES DIFFERENT METHOD FOR CARDINALITY
key = canonical_name + " cardinality"
es_query.aggs[key].cardinality.script = abs_value.to_ruby()
s.pull = key + ".value"
elif s.aggregate == "stats":
# REGULAR STATS
stats_name = literal_field(canonical_name)
es_query.aggs[stats_name].extended_stats.script = abs_value.to_ruby()
# GET MEDIAN TOO!
median_name = literal_field(canonical_name + " percentile")
es_query.aggs[median_name].percentiles.script = abs_value.to_ruby()
es_query.aggs[median_name].percentiles.percents += [50]
s.pull = {
"count": stats_name + ".count",
"sum": stats_name + ".sum",
"min": stats_name + ".min",
"max": stats_name + ".max",
"avg": stats_name + ".avg",
"sos": stats_name + ".sum_of_squares",
"std": stats_name + ".std_deviation",
"var": stats_name + ".variance",
"median": median_name + ".values.50\.0"
}
elif s.aggregate=="union":
# USE TERMS AGGREGATE TO SIMULATE union
stats_name = literal_field(canonical_name)
es_query.aggs[stats_name].terms.script_field = abs_value.to_ruby()
s.pull = stats_name + ".buckets.key"
else:
# PULL VALUE OUT OF THE stats AGGREGATE
s.pull = canonical_name + "." + aggregates1_4[s.aggregate]
es_query.aggs[canonical_name].extended_stats.script = abs_value.to_ruby()
decoders = get_decoders_by_depth(query)
start = 0
vars_ = query.where.vars()
#<TERRIBLE SECTION> THIS IS WHERE WE WEAVE THE where CLAUSE WITH nested
split_where = split_expression_by_depth(query.where, schema=frum.schema)
if len(split_field(frum.name)) > 1:
if any(split_where[2::]):
Log.error("Where clause is too deep")
for d in decoders[1]:
es_query = d.append_query(es_query, start)
start += d.num_columns
if split_where[1]:
#TODO: INCLUDE FILTERS ON EDGES
filter_ = simplify_esfilter(AndOp("and", split_where[1]).to_esfilter())
es_query = Data(
aggs={"_filter": set_default({"filter": filter_}, es_query)}
)
es_query = wrap({
"aggs": {"_nested": set_default(
{
"nested": {
"path": frum.query_path
}
},
es_query
)}
})
else:
if any(split_where[1::]):
Log.error("Where clause is too deep")
if decoders:
for d in jx.reverse(decoders[0]):
es_query = d.append_query(es_query, start)
start += d.num_columns
if split_where[0]:
#TODO: INCLUDE FILTERS ON EDGES
filter = simplify_esfilter(AndOp("and", split_where[0]).to_esfilter())
es_query = Data(
aggs={"_filter": set_default({"filter": filter}, es_query)}
)
# </TERRIBLE SECTION>
if not es_query:
es_query = wrap({"query": {"match_all": {}}})
es_query.size = 0
with Timer("ES query time") as es_duration:
result = es09.util.post(es, es_query, query.limit)
try:
format_time = Timer("formatting")
with format_time:
decoders = [d for ds in decoders for d in ds]
result.aggregations.doc_count = coalesce(result.aggregations.doc_count, result.hits.total) # IT APPEARS THE OLD doc_count IS GONE
formatter, groupby_formatter, aggop_formatter, mime_type = format_dispatch[query.format]
if query.edges:
output = formatter(decoders, result.aggregations, start, query, select)
elif query.groupby:
output = groupby_formatter(decoders, result.aggregations, start, query, select)
else:
output = aggop_formatter(decoders, result.aggregations, start, query, select)
output.meta.timing.formatting = format_time.duration
output.meta.timing.es_search = es_duration.duration
output.meta.content_type = mime_type
output.meta.es_query = es_query
return output
except Exception as e:
if query.format not in format_dispatch:
Log.error("Format {{format|quote}} not supported yet", format=query.format, cause=e)
Log.error("Some problem", e)
def parse(json, query_path, expected_vars=NO_VARS):
"""
INTENDED TO TREAT JSON AS A STREAM; USING MINIMAL MEMORY WHILE IT ITERATES
THROUGH THE STRUCTURE. ASSUMING THE JSON IS LARGE, AND HAS A HIGH LEVEL
ARRAY STRUCTURE, IT WILL yield EACH OBJECT IN THAT ARRAY. NESTED ARRAYS
ARE HANDLED BY REPEATING THE PARENT PROPERTIES FOR EACH MEMBER OF THE
NESTED ARRAY. DEEPER NESTED PROPERTIES ARE TREATED AS PRIMITIVE VALUES;
THE STANDARD JSON DECODER IS USED.
LARGE MANY-PROPERTY OBJECTS CAN BE HANDLED BY `items()`
:param json: SOME STRING-LIKE STRUCTURE THAT CAN ASSUME WE LOOK AT
ONE CHARACTER AT A TIME, IN ORDER
:param query_path: A DOT-SEPARATED STRING INDICATING THE PATH TO THE
NESTED ARRAY OPTIONALLY, {"items":query_path} TO
FURTHER ITERATE OVER PROPERTIES OF OBJECTS FOUND AT
query_path
:param expected_vars: REQUIRED PROPERTY NAMES, USED TO DETERMINE IF
MORE-THAN-ONE PASS IS REQUIRED
:return: RETURNS AN ITERATOR OVER ALL OBJECTS FROM ARRAY LOCATED AT query_path
"""
if hasattr(json, "read"):
# ASSUME IT IS A STREAM
temp = json
def get_more():
return temp.read(MIN_READ_SIZE)
json = List_usingStream(get_more)
elif hasattr(json, "__call__"):
json = List_usingStream(json)
elif isinstance(json, GeneratorType):
json = List_usingStream(json.next)
else:
Log.error(
"Expecting json to be a stream, or a function that will return more bytes"
)
def _iterate_list(index, c, parent_path, path, expected_vars):
c, index = skip_whitespace(index)
if c == b']':
yield index
return
while True:
if not path:
index = _assign_token(index, c, expected_vars)
c, index = skip_whitespace(index)
if c == b']':
yield index
_done(parent_path)
return
elif c == b',':
yield index
c, index = skip_whitespace(index)
else:
for index in _decode_token(index, c, parent_path, path,
expected_vars):
c, index = skip_whitespace(index)
if c == b']':
yield index
_done(parent_path)
return
elif c == b',':
yield index
c, index = skip_whitespace(index)
def _done(parent_path):
if len(parent_path) < len(done[0]):
done[0] = parent_path
def _decode_object(index, c, parent_path, query_path, expected_vars):
if "." in expected_vars:
if len(done[0]) <= len(parent_path) and all(
d == p for d, p in zip(done[0], parent_path)):
Log.error("Can not pick up more variables, iterator is done")
if query_path:
Log.error("Can not extract objects that contain the iteration",
var=join_field(query_path))
index = _assign_token(index, c, expected_vars)
# c, index = skip_whitespace(index)
yield index
return
did_yield = False
while True:
c, index = skip_whitespace(index)
if c == b',':
continue
elif c == b'"':
name, index = simple_token(index, c)
c, index = skip_whitespace(index)
if c != b':':
Log.error("Expecting colon")
c, index = skip_whitespace(index)
child_expected = needed(name, expected_vars)
child_path = parent_path + [name]
if any(child_expected):
if not query_path:
index = _assign_token(index, c, child_expected)
elif query_path[0] == name:
for index in _decode_token(index, c, child_path,
query_path[1:],
child_expected):
did_yield = True
yield index
else:
if len(done[0]) <= len(child_path):
Log.error(
"Can not pick up more variables, iterator over {{path}} is done",
path=join_field(done[0]))
index = _assign_token(index, c, child_expected)
elif query_path and query_path[0] == name:
for index in _decode_token(index, c, child_path,
query_path[1:], child_expected):
yield index
else:
index = jump_to_end(index, c)
elif c == b"}":
if not did_yield:
yield index
break
def set_destination(expected_vars, value):
for i, e in enumerate(expected_vars):
if e is None:
pass
elif e == ".":
destination[i] = value
elif is_data(value):
destination[i] = value[e]
else:
destination[i] = Null
def _decode_object_items(index, c, parent_path, query_path, expected_vars):
"""
ITERATE THROUGH THE PROPERTIES OF AN OBJECT
"""
c, index = skip_whitespace(index)
num_items = 0
while True:
if c == b',':
c, index = skip_whitespace(index)
elif c == b'"':
name, index = simple_token(index, c)
if "name" in expected_vars:
for i, e in enumerate(expected_vars):
if e == "name":
destination[i] = name
c, index = skip_whitespace(index)
if c != b':':
Log.error("Expecting colon")
c, index = skip_whitespace(index)
child_expected = needed("value", expected_vars)
index = _assign_token(index, c, child_expected)
c, index = skip_whitespace(index)
DEBUG and not num_items % 1000 and Log.note(
"{{num}} items iterated", num=num_items)
yield index
num_items += 1
elif c == b"}":
break
def _decode_token(index, c, parent_path, query_path, expected_vars):
if c == b'{':
if query_path and query_path[0] == "$items":
if any(expected_vars):
for index in _decode_object_items(index, c, parent_path,
query_path[1:],
expected_vars):
yield index
else:
index = jump_to_end(index, c)
yield index
elif not any(expected_vars):
index = jump_to_end(index, c)
yield index
else:
for index in _decode_object(index, c, parent_path, query_path,
expected_vars):
yield index
elif c == b'[':
for index in _iterate_list(index, c, parent_path, query_path,
expected_vars):
yield index
else:
index = _assign_token(index, c, expected_vars)
yield index
def _assign_token(index, c, expected_vars):
if not any(expected_vars):
return jump_to_end(index, c)
value, index = simple_token(index, c)
set_destination(expected_vars, value)
return index
def jump_to_end(index, c):
"""
DO NOT PROCESS THIS JSON OBJECT, JUST RETURN WHERE IT ENDS
"""
if c == b'"':
while True:
c = json[index]
index += 1
if c == b'\\':
index += 1
elif c == b'"':
break
return index
elif c not in b"[{":
while True:
c = json[index]
index += 1
if c in b',]}':
break
return index - 1
# OBJECTS AND ARRAYS ARE MORE INVOLVED
stack = [None] * 1024
stack[0] = CLOSE[c]
i = 0 # FOR INDEXING THE STACK
while True:
c = json[index]
index += 1
if c == b'"':
while True:
c = json[index]
index += 1
if c == b'\\':
index += 1
elif c == b'"':
break
elif c in b'[{':
i += 1
stack[i] = CLOSE[c]
elif c == stack[i]:
i -= 1
if i == -1:
return index # FOUND THE MATCH! RETURN
elif c in b']}':
Log.error("expecting {{symbol}}", symbol=stack[i])
def simple_token(index, c):
if c == b'"':
json.mark(index - 1)
while True:
c = json[index]
index += 1
if c == b"\\":
index += 1
elif c == b'"':
break
return json_decoder(json.release(index).decode("utf8")), index
elif c in b"{[":
json.mark(index - 1)
index = jump_to_end(index, c)
value = wrap(json_decoder(json.release(index).decode("utf8")))
return value, index
elif c == b"t" and json.slice(index, index + 3) == b"rue":
return True, index + 3
elif c == b"n" and json.slice(index, index + 3) == b"ull":
return None, index + 3
elif c == b"f" and json.slice(index, index + 4) == b"alse":
return False, index + 4
else:
json.mark(index - 1)
while True:
c = json[index]
if c in b',]}':
break
index += 1
text = json.release(index)
try:
return float(text), index
except Exception:
Log.error("Not a known JSON primitive: {{text|quote}}",
text=text)
def skip_whitespace(index):
"""
RETURN NEXT NON-WHITESPACE CHAR, AND ITS INDEX
"""
c = json[index]
while c in WHITESPACE:
index += 1
c = json[index]
return c, index + 1
if is_data(query_path) and query_path.get("items"):
path_list = split_field(query_path.get("items")) + [
"$items"
] # INSERT A MARKER SO THAT OBJECT IS STREAM DECODED
else:
path_list = split_field(query_path)
destination = [None] * len(expected_vars)
c, index = skip_whitespace(0)
done = [path_list + [None]]
for _ in _decode_token(index, c, [], path_list, expected_vars):
output = Data()
for i, e in enumerate(expected_vars):
output[e] = destination[i]
yield output
def __init__(self, db):
self.db = db
self._snowflakes = Data(
) # MAP FROM BASE TABLE TO LIST OF NESTED PATH TUPLES
self.columns = ColumnList(db)
def es_aggsop(es, frum, query):
query = query.copy() # WE WILL MARK UP THIS QUERY
schema = frum.schema
select = listwrap(query.select)
es_query = Data()
new_select = Data() # MAP FROM canonical_name (USED FOR NAMES IN QUERY) TO SELECT MAPPING
formula = []
for s in select:
if s.aggregate == "count" and isinstance(s.value, Variable) and s.value.var == ".":
if schema.query_path == ".":
s.pull = jx_expression_to_function("doc_count")
else:
s.pull = jx_expression_to_function({"coalesce": ["_nested.doc_count", "doc_count", 0]})
elif isinstance(s.value, Variable):
if s.aggregate == "count":
new_select["count_"+literal_field(s.value.var)] += [s]
else:
new_select[literal_field(s.value.var)] += [s]
elif s.aggregate:
formula.append(s)
for canonical_name, many in new_select.items():
for s in many:
columns = frum.schema.values(s.value.var)
if s.aggregate == "count":
canonical_names = []
for column in columns:
cn = literal_field(column.es_column + "_count")
if column.jx_type == EXISTS:
canonical_names.append(cn + ".doc_count")
es_query.aggs[cn].filter.range = {column.es_column: {"gt": 0}}
else:
canonical_names.append(cn+ ".value")
es_query.aggs[cn].value_count.field = column.es_column
if len(canonical_names) == 1:
s.pull = jx_expression_to_function(canonical_names[0])
else:
s.pull = jx_expression_to_function({"add": canonical_names})
elif s.aggregate == "median":
if len(columns) > 1:
Log.error("Do not know how to count columns with more than one type (script probably)")
# ES USES DIFFERENT METHOD FOR PERCENTILES
key = literal_field(canonical_name + " percentile")
es_query.aggs[key].percentiles.field = columns[0].es_column
es_query.aggs[key].percentiles.percents += [50]
s.pull = jx_expression_to_function(key + ".values.50\\.0")
elif s.aggregate == "percentile":
if len(columns) > 1:
Log.error("Do not know how to count columns with more than one type (script probably)")
# ES USES DIFFERENT METHOD FOR PERCENTILES
key = literal_field(canonical_name + " percentile")
if isinstance(s.percentile, text_type) or s.percetile < 0 or 1 < s.percentile:
Log.error("Expecting percentile to be a float from 0.0 to 1.0")
percent = Math.round(s.percentile * 100, decimal=6)
es_query.aggs[key].percentiles.field = columns[0].es_column
es_query.aggs[key].percentiles.percents += [percent]
es_query.aggs[key].percentiles.tdigest.compression = 2
s.pull = jx_expression_to_function(key + ".values." + literal_field(text_type(percent)))
elif s.aggregate == "cardinality":
canonical_names = []
for column in columns:
cn = literal_field(column.es_column + "_cardinality")
canonical_names.append(cn)
es_query.aggs[cn].cardinality.field = column.es_column
if len(columns) == 1:
s.pull = jx_expression_to_function(canonical_names[0] + ".value")
else:
s.pull = jx_expression_to_function({"add": [cn + ".value" for cn in canonical_names], "default": 0})
elif s.aggregate == "stats":
if len(columns) > 1:
Log.error("Do not know how to count columns with more than one type (script probably)")
# REGULAR STATS
stats_name = literal_field(canonical_name)
es_query.aggs[stats_name].extended_stats.field = columns[0].es_column
# GET MEDIAN TOO!
median_name = literal_field(canonical_name + "_percentile")
es_query.aggs[median_name].percentiles.field = columns[0].es_column
es_query.aggs[median_name].percentiles.percents += [50]
s.pull = get_pull_stats(stats_name, median_name)
elif s.aggregate == "union":
pulls = []
for column in columns:
script = {"scripted_metric": {
'init_script': 'params._agg.terms = new HashSet()',
'map_script': 'for (v in doc['+quote(column.es_column)+'].values) params._agg.terms.add(v);',
'combine_script': 'return params._agg.terms.toArray()',
'reduce_script': 'HashSet output = new HashSet(); for (a in params._aggs) { if (a!=null) for (v in a) {output.add(v)} } return output.toArray()',
}}
stats_name = encode_property(column.es_column)
if column.nested_path[0] == ".":
es_query.aggs[stats_name] = script
pulls.append(jx_expression_to_function(stats_name + ".value"))
else:
es_query.aggs[stats_name] = {
"nested": {"path": column.nested_path[0]},
"aggs": {"_nested": script}
}
pulls.append(jx_expression_to_function(stats_name + "._nested.value"))
if len(pulls) == 0:
s.pull = NULL
elif len(pulls) == 1:
s.pull = pulls[0]
else:
s.pull = lambda row: UNION(p(row) for p in pulls)
else:
if len(columns) > 1:
Log.error("Do not know how to count columns with more than one type (script probably)")
elif len(columns) <1:
# PULL VALUE OUT OF THE stats AGGREGATE
s.pull = jx_expression_to_function({"null":{}})
else:
# PULL VALUE OUT OF THE stats AGGREGATE
es_query.aggs[literal_field(canonical_name)].extended_stats.field = columns[0].es_column
s.pull = jx_expression_to_function({"coalesce": [literal_field(canonical_name) + "." + aggregates[s.aggregate], s.default]})
for i, s in enumerate(formula):
canonical_name = literal_field(s.name)
if isinstance(s.value, TupleOp):
if s.aggregate == "count":
# TUPLES ALWAYS EXIST, SO COUNTING THEM IS EASY
s.pull = "doc_count"
elif s.aggregate in ('max', 'maximum', 'min', 'minimum'):
if s.aggregate in ('max', 'maximum'):
dir = 1
op = "max"
else:
dir = -1
op = 'min'
nully = TupleOp("tuple", [NULL]*len(s.value.terms)).partial_eval().to_es_script(schema).expr
selfy = s.value.partial_eval().to_es_script(schema).expr
script = {"scripted_metric": {
'init_script': 'params._agg.best = ' + nully + ';',
'map_script': 'params._agg.best = ' + expand_template(MAX_OF_TUPLE, {"expr1": "params._agg.best", "expr2": selfy, "dir": dir, "op": op}) + ";",
'combine_script': 'return params._agg.best',
'reduce_script': 'return params._aggs.stream().max(' + expand_template(COMPARE_TUPLE, {"dir": dir, "op": op}) + ').get()',
}}
if schema.query_path[0] == ".":
es_query.aggs[canonical_name] = script
s.pull = jx_expression_to_function(literal_field(canonical_name) + ".value")
else:
es_query.aggs[canonical_name] = {
"nested": {"path": schema.query_path[0]},
"aggs": {"_nested": script}
}
s.pull = jx_expression_to_function(literal_field(canonical_name) + "._nested.value")
else:
Log.error("{{agg}} is not a supported aggregate over a tuple", agg=s.aggregate)
elif s.aggregate == "count":
es_query.aggs[literal_field(canonical_name)].value_count.script = s.value.partial_eval().to_es_script(schema).script(schema)
s.pull = jx_expression_to_function(literal_field(canonical_name) + ".value")
elif s.aggregate == "median":
# ES USES DIFFERENT METHOD FOR PERCENTILES THAN FOR STATS AND COUNT
key = literal_field(canonical_name + " percentile")
es_query.aggs[key].percentiles.script = s.value.to_es_script(schema).script(schema)
es_query.aggs[key].percentiles.percents += [50]
s.pull = jx_expression_to_function(key + ".values.50\\.0")
elif s.aggregate == "percentile":
# ES USES DIFFERENT METHOD FOR PERCENTILES THAN FOR STATS AND COUNT
key = literal_field(canonical_name + " percentile")
percent = Math.round(s.percentile * 100, decimal=6)
es_query.aggs[key].percentiles.script = s.value.to_es_script(schema).script(schema)
es_query.aggs[key].percentiles.percents += [percent]
s.pull = jx_expression_to_function(key + ".values." + literal_field(text_type(percent)))
elif s.aggregate == "cardinality":
# ES USES DIFFERENT METHOD FOR CARDINALITY
key = canonical_name + " cardinality"
es_query.aggs[key].cardinality.script = s.value.to_es_script(schema).script(schema)
s.pull = jx_expression_to_function(key + ".value")
elif s.aggregate == "stats":
# REGULAR STATS
stats_name = literal_field(canonical_name)
es_query.aggs[stats_name].extended_stats.script = s.value.to_es_script(schema).script(schema)
# GET MEDIAN TOO!
median_name = literal_field(canonical_name + " percentile")
es_query.aggs[median_name].percentiles.script = s.value.to_es_script(schema).script(schema)
es_query.aggs[median_name].percentiles.percents += [50]
s.pull = get_pull_stats(stats_name, median_name)
elif s.aggregate == "union":
# USE TERMS AGGREGATE TO SIMULATE union
stats_name = literal_field(canonical_name)
es_query.aggs[stats_name].terms.script_field = s.value.to_es_script(schema).script(schema)
s.pull = jx_expression_to_function(stats_name + ".buckets.key")
else:
# PULL VALUE OUT OF THE stats AGGREGATE
s.pull = jx_expression_to_function(canonical_name + "." + aggregates[s.aggregate])
es_query.aggs[canonical_name].extended_stats.script = s.value.to_es_script(schema).script(schema)
decoders = get_decoders_by_depth(query)
start = 0
# <TERRIBLE SECTION> THIS IS WHERE WE WEAVE THE where CLAUSE WITH nested
split_where = split_expression_by_depth(query.where, schema=frum.schema)
if len(split_field(frum.name)) > 1:
if any(split_where[2::]):
Log.error("Where clause is too deep")
for d in decoders[1]:
es_query = d.append_query(es_query, start)
start += d.num_columns
if split_where[1]:
#TODO: INCLUDE FILTERS ON EDGES
filter_ = AndOp("and", split_where[1]).to_esfilter(schema)
es_query = Data(
aggs={"_filter": set_default({"filter": filter_}, es_query)}
)
es_query = wrap({
"aggs": {"_nested": set_default(
{"nested": {"path": schema.query_path[0]}},
es_query
)}
})
else:
if any(split_where[1::]):
Log.error("Where clause is too deep")
if decoders:
for d in jx.reverse(decoders[0]):
es_query = d.append_query(es_query, start)
start += d.num_columns
if split_where[0]:
#TODO: INCLUDE FILTERS ON EDGES
filter = AndOp("and", split_where[0]).to_esfilter(schema)
es_query = Data(
aggs={"_filter": set_default({"filter": filter}, es_query)}
)
# </TERRIBLE SECTION>
if not es_query:
es_query = wrap({"query": {"match_all": {}}})
es_query.size = 0
with Timer("ES query time") as es_duration:
result = es_post(es, es_query, query.limit)
try:
format_time = Timer("formatting")
with format_time:
decoders = [d for ds in decoders for d in ds]
result.aggregations.doc_count = coalesce(result.aggregations.doc_count, result.hits.total) # IT APPEARS THE OLD doc_count IS GONE
formatter, groupby_formatter, aggop_formatter, mime_type = format_dispatch[query.format]
if query.edges:
output = formatter(decoders, result.aggregations, start, query, select)
elif query.groupby:
output = groupby_formatter(decoders, result.aggregations, start, query, select)
else:
output = aggop_formatter(decoders, result.aggregations, start, query, select)
output.meta.timing.formatting = format_time.duration
output.meta.timing.es_search = es_duration.duration
output.meta.content_type = mime_type
output.meta.es_query = es_query
return output
except Exception as e:
if query.format not in format_dispatch:
Log.error("Format {{format|quote}} not supported yet", format=query.format, cause=e)
Log.error("Some problem", cause=e)
def request(method, url, zip=None, retry=None, **kwargs):
"""
JUST LIKE requests.request() BUT WITH DEFAULT HEADERS AND FIXES
DEMANDS data IS ONE OF:
* A JSON-SERIALIZABLE STRUCTURE, OR
* LIST OF JSON-SERIALIZABLE STRUCTURES, OR
* None
Parameters
* zip - ZIP THE REQUEST BODY, IF BIG ENOUGH
* json - JSON-SERIALIZABLE STRUCTURE
* retry - {"times": x, "sleep": y} STRUCTURE
THE BYTE_STRINGS (b"") ARE NECESSARY TO PREVENT httplib.py FROM **FREAKING OUT**
IT APPEARS requests AND httplib.py SIMPLY CONCATENATE STRINGS BLINDLY, WHICH
INCLUDES url AND headers
"""
global _warning_sent
if not default_headers and not _warning_sent:
_warning_sent = True
Log.warning(
"The pyLibrary.env.http module was meant to add extra "
"default headers to all requests, specifically the 'Referer' "
"header with a URL to the project. Use the `pyLibrary.debug.constants.set()` "
"function to set `pyLibrary.env.http.default_headers`"
)
if isinstance(url, list):
# TRY MANY URLS
failures = []
for remaining, u in jx.countdown(url):
try:
response = request(method, u, zip=zip, retry=retry, **kwargs)
if Math.round(response.status_code, decimal=-2) not in [400, 500]:
return response
if not remaining:
return response
except Exception as e:
e = Except.wrap(e)
failures.append(e)
Log.error("Tried {{num}} urls", num=len(url), cause=failures)
if b"session" in kwargs:
session = kwargs[b"session"]
del kwargs[b"session"]
else:
session = sessions.Session()
session.headers.update(default_headers)
if zip is None:
zip = ZIP_REQUEST
if isinstance(url, unicode):
# httplib.py WILL **FREAK OUT** IF IT SEES ANY UNICODE
url = url.encode("ascii")
_to_ascii_dict(kwargs)
timeout = kwargs[b'timeout'] = coalesce(kwargs.get(b'timeout'), default_timeout)
if retry == None:
retry = Data(times=1, sleep=0)
elif isinstance(retry, Number):
retry = Data(times=retry, sleep=1)
else:
retry = wrap(retry)
if isinstance(retry.sleep, Duration):
retry.sleep = retry.sleep.seconds
set_default(retry, {"times": 1, "sleep": 0})
if b'json' in kwargs:
kwargs[b'data'] = convert.value2json(kwargs[b'json']).encode("utf8")
del kwargs[b'json']
try:
headers = kwargs[b"headers"] = unwrap(coalesce(wrap(kwargs)[b"headers"], {}))
set_default(headers, {b"accept-encoding": b"compress, gzip"})
if zip and len(coalesce(kwargs.get(b"data"))) > 1000:
compressed = convert.bytes2zip(kwargs[b"data"])
headers[b'content-encoding'] = b'gzip'
kwargs[b"data"] = compressed
_to_ascii_dict(headers)
else:
_to_ascii_dict(headers)
except Exception as e:
Log.error("Request setup failure on {{url}}", url=url, cause=e)
errors = []
for r in range(retry.times):
if r:
Till(seconds=retry.sleep).wait()
try:
if DEBUG:
Log.note("http {{method}} to {{url}}", method=method, url=url)
return session.request(method=method, url=url, **kwargs)
except Exception as e:
errors.append(Except.wrap(e))
if " Read timed out." in errors[0]:
Log.error("Tried {{times}} times: Timeout failure (timeout was {{timeout}}", timeout=timeout, times=retry.times, cause=errors[0])
else:
Log.error("Tried {{times}} times: Request failure of {{url}}", url=url, times=retry.times, cause=errors[0])
