def main():
try:
settings = startup.read_settings(defs=[{
"name": ["--id"],
"help": "id (prefix, really) to process",
"type": str,
"dest": "id",
"required": False
}])
constants.set(settings.constants)
Log.start(settings.debug)
queries.config.default = {
"type": "elasticsearch",
"settings": settings.elasticsearch.copy()
}
if settings.args.id:
work_queue = Queue("local work queue")
work_queue.extend(parse_id_argument(settings.args.id))
else:
work_queue = aws.Queue(settings=settings.work_queue)
Log.note("Listen to queue {{queue}}, and read off of {{s3}}",
queue=settings.work_queue.name,
s3=settings.source.bucket)
es = MultiDayIndex(settings.elasticsearch, queue_size=100000)
threads = []
please_stop = Signal()
for _ in range(settings.threads):
p = Thread.run("copy to es",
copy2es,
es,
settings,
work_queue,
please_stop=please_stop)
threads.append(p)
def monitor_progress(please_stop):
while not please_stop:
Log.note("Remaining: {{num}}", num=len(work_queue))
Thread.sleep(seconds=10)
Thread.run(name="monitor progress",
target=monitor_progress,
please_stop=please_stop)
aws.capture_termination_signal(please_stop)
Thread.wait_for_shutdown_signal(please_stop=please_stop,
allow_exit=True)
please_stop.go()
Log.note("Shutdown started")
except Exception, e:
Log.error("Problem with etl", e)
def find_changeset(self, revision, please_stop=False):
locker = Lock()
output = []
queue = Queue("branches", max=2000)
queue.extend(self.branches)
queue.add(Thread.STOP)
problems = []
def _find(please_stop):
for b in queue:
if please_stop:
return
try:
url = b.url + "json-info?node=" + revision
response = http.get(url, timeout=30)
if response.status_code == 200:
with locker:
output.append(b)
Log.note("{{revision}} found at {{url}}", url=url, revision=revision)
except Exception, f:
problems.append(f)
class FromESMetadata(Schema):
"""
QUERY THE METADATA
"""
def __new__(cls, *args, **kwargs):
global singlton
if singlton:
return singlton
else:
singlton = object.__new__(cls)
return singlton
@use_settings
def __init__(self,
host,
index,
alias=None,
name=None,
port=9200,
settings=None):
global _elasticsearch
if hasattr(self, "settings"):
return
from pyLibrary.queries.containers.lists import ListContainer
from pyLibrary.env import elasticsearch as _elasticsearch
self.settings = settings
self.default_name = coalesce(name, alias, index)
self.default_es = _elasticsearch.Cluster(settings=settings)
self.todo = Queue("refresh metadata", max=100000, unique=True)
self.meta = Dict()
table_columns = metadata_tables()
column_columns = metadata_columns()
self.meta.tables = ListContainer(
"meta.tables", [], wrap({c.name: c
for c in table_columns}))
self.meta.columns = ListContainer(
"meta.columns", [], wrap({c.name: c
for c in column_columns}))
self.meta.columns.insert(column_columns)
self.meta.columns.insert(table_columns)
# TODO: fix monitor so it does not bring down ES
if ENABLE_META_SCAN:
self.worker = Thread.run("refresh metadata", self.monitor)
else:
self.worker = Thread.run("refresh metadata", self.not_monitor)
return
@property
def query_path(self):
return None
@property
def url(self):
return self.default_es.path + "/" + self.default_name.replace(".", "/")
def get_table(self, table_name):
with self.meta.tables.locker:
return self.meta.tables.query(
{"where": {
"eq": {
"name": table_name
}
}})
def _upsert_column(self, c):
# ASSUMING THE self.meta.columns.locker IS HAD
existing_columns = [
r for r in self.meta.columns.data
if r.table == c.table and r.name == c.name
]
if not existing_columns:
self.meta.columns.add(c)
Log.note("todo: {{table}}.{{column}}",
table=c.table,
column=c.es_column)
self.todo.add(c)
# MARK meta.columns AS DIRTY TOO
cols = [
r for r in self.meta.columns.data if r.table == "meta.columns"
]
for cc in cols:
cc.partitions = cc.cardinality = None
cc.last_updated = Date.now()
self.todo.extend(cols)
else:
canonical = existing_columns[0]
if canonical.relative and not c.relative:
return # RELATIVE COLUMNS WILL SHADOW ABSOLUTE COLUMNS
for key in Column.__slots__:
canonical[key] = c[key]
Log.note("todo: {{table}}.{{column}}",
table=canonical.table,
column=canonical.es_column)
self.todo.add(canonical)
def _get_columns(self, table=None, metadata=None):
# TODO: HANDLE MORE THEN ONE ES, MAP TABLE SHORT_NAME TO ES INSTANCE
if not metadata:
metadata = self.default_es.get_metadata(force=True)
def parse_all(please_stop):
for abs_index, meta in jx.sort(metadata.indices.items(), {
"value": 0,
"sort": -1
}):
if meta.index != abs_index:
continue
for _, properties in meta.mappings.items():
if please_stop:
return
self._parse_properties(abs_index, properties, meta)
if table:
for abs_index, meta in jx.sort(metadata.indices.items(), {
"value": 0,
"sort": -1
}):
if table == meta.index:
for _, properties in meta.mappings.items():
self._parse_properties(abs_index, properties, meta)
return
if table == abs_index:
self._get_columns(table=meta.index, metadata=metadata)
return
else:
self.parser = Thread.run("parse properties", parse_all)
def _parse_properties(self, abs_index, properties, meta):
abs_columns = _elasticsearch.parse_properties(abs_index, None,
properties.properties)
abs_columns = abs_columns.filter( # TODO: REMOVE WHEN jobs PROPERTY EXPLOSION IS CONTAINED
lambda r: not r.es_column.startswith("other.") and not r.es_column.
startswith("previous_values.cf_") and not r.es_index.startswith(
"debug"))
with Timer("upserting {{num}} columns", {"num": len(abs_columns)},
debug=DEBUG):
def add_column(c, query_path):
c.last_updated = Date.now()
if query_path:
c.table = c.es_index + "." + query_path.last()
else:
c.table = c.es_index
with self.meta.columns.locker:
self._upsert_column(c)
for alias in meta.aliases:
c = copy(c)
if query_path:
c.table = alias + "." + query_path.last()
else:
c.table = alias
self._upsert_column(c)
# EACH query_path IS A LIST OF EVER-INCREASING PATHS THROUGH EACH NESTED LEVEL
query_paths = wrap([[c.es_column] for c in abs_columns
if c.type == "nested"])
for a, b in itertools.product(query_paths, query_paths):
aa = a.last()
bb = b.last()
if aa and bb.startswith(aa):
for i, b_prefix in enumerate(b):
if len(b_prefix) < len(aa):
continue
if aa == b_prefix:
break # SPLIT ALREADY FOUND
b.insert(0, aa)
break
query_paths.append([])
for c in abs_columns:
# ADD RELATIVE COLUMNS
full_path = listwrap(c.nested_path)
abs_depth = len(full_path)
abs_parent = coalesce(full_path.last(), "")
for query_path in query_paths:
rel_depth = len(query_path)
# ABSOLUTE
add_column(copy(c), query_path)
cc = copy(c)
cc.relative = True
if not query_path:
add_column(cc, query_path)
continue
rel_parent = query_path.last()
if c.es_column.startswith(rel_parent + "."):
cc.name = c.es_column[len(rel_parent) + 1:]
add_column(cc, query_path)
elif c.es_column == rel_parent:
cc.name = "."
add_column(cc, query_path)
elif not abs_parent:
# THIS RELATIVE NAME (..o) ALSO NEEDS A RELATIVE NAME (o)
# AND THEN REMOVE THE SHADOWED
cc.name = "." + ("." *
(rel_depth - abs_depth)) + c.es_column
add_column(cc, query_path)
elif rel_parent.startswith(abs_parent + "."):
cc.name = "." + ("." *
(rel_depth - abs_depth)) + c.es_column
add_column(cc, query_path)
elif rel_parent != abs_parent:
# SIBLING NESTED PATHS ARE INVISIBLE
pass
else:
Log.error("logic error")
def query(self, _query):
return self.meta.columns.query(
QueryOp(
set_default(
{
"from": self.meta.columns,
"sort": ["table", "name"]
}, _query.as_dict())))
def get_columns(self,
table_name,
column_name=None,
fail_when_not_found=False):
"""
RETURN METADATA COLUMNS
"""
try:
with self.meta.columns.locker:
columns = [
c for c in self.meta.columns.data
if c.table == table_name and (
column_name is None or c.name == column_name)
]
if columns:
columns = jx.sort(columns, "name")
if fail_when_not_found:
# AT LEAST WAIT FOR THE COLUMNS TO UPDATE
while len(self.todo) and not all(
columns.get("last_updated")):
Log.note(
"waiting for columns to update {{columns|json}}",
columns=[
c.table + "." + c.es_column for c in columns
if not c.last_updated
])
Thread.sleep(seconds=1)
return columns
elif all(columns.get("last_updated")):
return columns
except Exception, e:
Log.error("Not expected", cause=e)
if fail_when_not_found:
if column_name:
Log.error("no columns matching {{table}}.{{column}}",
table=table_name,
column=column_name)
else:
self._get_columns(table=table_name)
Log.error("no columns for {{table}}", table=table_name)
self._get_columns(table=join_field(split_field(table_name)[0:1]))
return self.get_columns(table_name=table_name,
column_name=column_name,
fail_when_not_found=True)
class FromESMetadata(Schema):
"""
QUERY THE METADATA
"""
def __new__(cls, *args, **kwargs):
global singlton
if singlton:
return singlton
else:
singlton = object.__new__(cls)
return singlton
@use_settings
def __init__(self, host, index, alias=None, name=None, port=9200, settings=None):
global _elasticsearch
if hasattr(self, "settings"):
return
from pyLibrary.queries.containers.lists import ListContainer
from pyLibrary.env import elasticsearch as _elasticsearch
self.settings = settings
self.default_name = coalesce(name, alias, index)
self.default_es = _elasticsearch.Cluster(settings=settings)
self.todo = Queue("refresh metadata", max=100000, unique=True)
self.meta=Dict()
table_columns = metadata_tables()
column_columns = metadata_columns()
self.meta.tables = ListContainer("meta.tables", [], wrap({c.name: c for c in table_columns}))
self.meta.columns = ListContainer("meta.columns", [], wrap({c.name: c for c in column_columns}))
self.meta.columns.insert(column_columns)
self.meta.columns.insert(table_columns)
# TODO: fix monitor so it does not bring down ES
if ENABLE_META_SCAN:
self.worker = Thread.run("refresh metadata", self.monitor)
else:
self.worker = Thread.run("refresh metadata", self.not_monitor)
return
@property
def query_path(self):
return None
@property
def url(self):
return self.default_es.path + "/" + self.default_name.replace(".", "/")
def get_table(self, table_name):
with self.meta.tables.locker:
return self.meta.tables.query({"where": {"eq": {"name": table_name}}})
def _upsert_column(self, c):
# ASSUMING THE self.meta.columns.locker IS HAD
existing_columns = [r for r in self.meta.columns.data if r.table == c.table and r.name == c.name]
if not existing_columns:
self.meta.columns.add(c)
Log.note("todo: {{table}}.{{column}}", table=c.table, column=c.es_column)
self.todo.add(c)
# MARK meta.columns AS DIRTY TOO
cols = [r for r in self.meta.columns.data if r.table == "meta.columns"]
for cc in cols:
cc.partitions = cc.cardinality = None
cc.last_updated = Date.now()
self.todo.extend(cols)
else:
canonical = existing_columns[0]
if canonical.relative and not c.relative:
return # RELATIVE COLUMNS WILL SHADOW ABSOLUTE COLUMNS
for key in Column.__slots__:
canonical[key] = c[key]
Log.note("todo: {{table}}.{{column}}", table=canonical.table, column=canonical.es_column)
self.todo.add(canonical)
def _get_columns(self, table=None, metadata=None):
# TODO: HANDLE MORE THEN ONE ES, MAP TABLE SHORT_NAME TO ES INSTANCE
if not metadata:
metadata = self.default_es.get_metadata(force=True)
def parse_all(please_stop):
for abs_index, meta in jx.sort(metadata.indices.items(), {"value": 0, "sort": -1}):
if meta.index != abs_index:
continue
for _, properties in meta.mappings.items():
if please_stop:
return
self._parse_properties(abs_index, properties, meta)
if table:
for abs_index, meta in jx.sort(metadata.indices.items(), {"value": 0, "sort": -1}):
if table == meta.index:
for _, properties in meta.mappings.items():
self._parse_properties(abs_index, properties, meta)
return
if table == abs_index:
self._get_columns(table=meta.index, metadata=metadata)
return
else:
self.parser = Thread.run("parse properties", parse_all)
def _parse_properties(self, abs_index, properties, meta):
abs_columns = _elasticsearch.parse_properties(abs_index, None, properties.properties)
abs_columns = abs_columns.filter( # TODO: REMOVE WHEN jobs PROPERTY EXPLOSION IS CONTAINED
lambda r: not r.es_column.startswith("other.") and
not r.es_column.startswith("previous_values.cf_") and
not r.es_index.startswith("debug")
)
with Timer("upserting {{num}} columns", {"num": len(abs_columns)}, debug=DEBUG):
def add_column(c, query_path):
c.last_updated = Date.now()
if query_path:
c.table = c.es_index + "." + query_path.last()
else:
c.table = c.es_index
with self.meta.columns.locker:
self._upsert_column(c)
for alias in meta.aliases:
c = copy(c)
if query_path:
c.table = alias + "." + query_path.last()
else:
c.table = alias
self._upsert_column(c)
# EACH query_path IS A LIST OF EVER-INCREASING PATHS THROUGH EACH NESTED LEVEL
query_paths = wrap([[c.es_column] for c in abs_columns if c.type == "nested"])
for a, b in itertools.product(query_paths, query_paths):
aa = a.last()
bb = b.last()
if aa and bb.startswith(aa):
for i, b_prefix in enumerate(b):
if len(b_prefix) < len(aa):
continue
if aa == b_prefix:
break # SPLIT ALREADY FOUND
b.insert(0, aa)
break
query_paths.append([])
for c in abs_columns:
# ADD RELATIVE COLUMNS
full_path = listwrap(c.nested_path)
abs_depth = len(full_path)
abs_parent = coalesce(full_path.last(), "")
for query_path in query_paths:
rel_depth = len(query_path)
# ABSOLUTE
add_column(copy(c), query_path)
cc = copy(c)
cc.relative = True
if not query_path:
add_column(cc, query_path)
continue
rel_parent = query_path.last()
if c.es_column.startswith(rel_parent+"."):
cc.name = c.es_column[len(rel_parent)+1:]
add_column(cc, query_path)
elif c.es_column == rel_parent:
cc.name = "."
add_column(cc, query_path)
elif not abs_parent:
# THIS RELATIVE NAME (..o) ALSO NEEDS A RELATIVE NAME (o)
# AND THEN REMOVE THE SHADOWED
cc.name = "." + ("." * (rel_depth - abs_depth)) + c.es_column
add_column(cc, query_path)
elif rel_parent.startswith(abs_parent+"."):
cc.name = "." + ("." * (rel_depth - abs_depth)) + c.es_column
add_column(cc, query_path)
elif rel_parent != abs_parent:
# SIBLING NESTED PATHS ARE INVISIBLE
pass
else:
Log.error("logic error")
def query(self, _query):
return self.meta.columns.query(QueryOp(set_default(
{
"from": self.meta.columns,
"sort": ["table", "name"]
},
_query.as_dict()
)))
def get_columns(self, table_name, column_name=None, fail_when_not_found=False):
"""
RETURN METADATA COLUMNS
"""
try:
with self.meta.columns.locker:
columns = [c for c in self.meta.columns.data if c.table == table_name and (column_name is None or c.name==column_name)]
if columns:
columns = jx.sort(columns, "name")
if fail_when_not_found:
# AT LEAST WAIT FOR THE COLUMNS TO UPDATE
while len(self.todo) and not all(columns.get("last_updated")):
Log.note("waiting for columns to update {{columns|json}}", columns=[c.table+"."+c.es_column for c in columns if not c.last_updated])
Thread.sleep(seconds=1)
return columns
elif all(columns.get("last_updated")):
return columns
except Exception, e:
Log.error("Not expected", cause=e)
if fail_when_not_found:
if column_name:
Log.error("no columns matching {{table}}.{{column}}", table=table_name, column=column_name)
else:
self._get_columns(table=table_name)
Log.error("no columns for {{table}}", table=table_name)
self._get_columns(table=join_field(split_field(table_name)[0:1]))
return self.get_columns(table_name=table_name, column_name=column_name, fail_when_not_found=True)
def loop(source, coverage_summary_index, settings, please_stop):
try:
cluster = elasticsearch.Cluster(source)
aliases = cluster.get_aliases()
candidates = []
for pairs in aliases:
if pairs.alias == source.index:
candidates.append(pairs.index)
candidates = jx.sort(candidates, {".": "desc"})
for index_name in candidates:
coverage_index = elasticsearch.Index(index=index_name, read_only=False, settings=source)
push_date_filter = unicode2Date(coverage_index.settings.index[-15::], elasticsearch.INDEX_DATE_FORMAT)
while not please_stop:
# IDENTIFY NEW WORK
Log.note("Working on index {{index}}", index=index_name)
coverage_index.refresh()
todo = http.post_json(settings.url, json={
"from": "coverage",
"groupby": ["source.file.name", "build.revision12"],
"where": {"and": [
{"missing": "source.method.name"},
{"missing": "source.file.min_line_siblings"},
{"gte": {"repo.push.date": push_date_filter}}
]},
"format": "list",
"limit": coalesce(settings.batch_size, 100)
})
if not todo.data:
break
queue = Queue("pending source files to review")
queue.extend(todo.data[0:coalesce(settings.batch_size, 100):])
threads = [
Thread.run(
"processor" + unicode(i),
process_batch,
queue,
coverage_index,
coverage_summary_index,
settings,
please_stop=please_stop
)
for i in range(NUM_THREAD)
]
# ADD STOP MESSAGE
queue.add(Thread.STOP)
# WAIT FOR THEM TO COMPLETE
for t in threads:
t.join()
please_stop.go()
return
except Exception, e:
Log.warning("Problem processing", cause=e)
class FromESMetadata(Schema):
"""
QUERY THE METADATA
"""
def __new__(cls, *args, **kwargs):
global singlton
if singlton:
return singlton
else:
singlton = object.__new__(cls)
return singlton
@use_settings
def __init__(self, host, index, alias=None, name=None, port=9200, settings=None):
global _elasticsearch
if hasattr(self, "settings"):
return
from pyLibrary.queries.containers.list_usingPythonList import ListContainer
from pyLibrary.env import elasticsearch as _elasticsearch
self.settings = settings
self.default_name = coalesce(name, alias, index)
self.default_es = _elasticsearch.Cluster(settings=settings)
self.todo = Queue("refresh metadata", max=100000, unique=True)
self.es_metadata = Null
self.last_es_metadata = Date.now()-OLD_METADATA
self.meta=Dict()
table_columns = metadata_tables()
column_columns = metadata_columns()
self.meta.tables = ListContainer("meta.tables", [], wrap({c.name: c for c in table_columns}))
self.meta.columns = ColumnList()
self.meta.columns.insert(column_columns)
self.meta.columns.insert(table_columns)
# TODO: fix monitor so it does not bring down ES
if ENABLE_META_SCAN:
self.worker = Thread.run("refresh metadata", self.monitor)
else:
self.worker = Thread.run("refresh metadata", self.not_monitor)
return
@property
def query_path(self):
return None
@property
def url(self):
return self.default_es.path + "/" + self.default_name.replace(".", "/")
def get_table(self, table_name):
with self.meta.tables.locker:
return wrap([t for t in self.meta.tables.data if t.name == table_name])
def _upsert_column(self, c):
# ASSUMING THE self.meta.columns.locker IS HAD
existing_columns = self.meta.columns.find(c.table, c.name)
if not existing_columns:
self.meta.columns.add(c)
self.todo.add(c)
if ENABLE_META_SCAN:
Log.note("todo: {{table}}::{{column}}", table=c.table, column=c.es_column)
# MARK meta.columns AS DIRTY TOO
cols = self.meta.columns.find("meta.columns", None)
for cc in cols:
cc.partitions = cc.cardinality = None
cc.last_updated = Date.now()
self.todo.extend(cols)
else:
canonical = existing_columns[0]
if canonical.relative and not c.relative:
return # RELATIVE COLUMNS WILL SHADOW ABSOLUTE COLUMNS
for key in Column.__slots__:
canonical[key] = c[key]
Log.note("todo: {{table}}::{{column}}", table=canonical.table, column=canonical.es_column)
self.todo.add(canonical)
def _get_columns(self, table=None):
# TODO: HANDLE MORE THEN ONE ES, MAP TABLE SHORT_NAME TO ES INSTANCE
meta = self.es_metadata.indices[table]
if not meta or self.last_es_metadata < Date.now() - OLD_METADATA:
self.es_metadata = self.default_es.get_metadata(force=True)
meta = self.es_metadata.indices[table]
for _, properties in meta.mappings.items():
self._parse_properties(meta.index, properties, meta)
def _parse_properties(self, abs_index, properties, meta):
abs_columns = _elasticsearch.parse_properties(abs_index, None, properties.properties)
abs_columns = abs_columns.filter( # TODO: REMOVE WHEN jobs PROPERTY EXPLOSION IS CONTAINED
lambda r: not r.es_column.startswith("other.") and
not r.es_column.startswith("previous_values.cf_") and
not r.es_index.startswith("debug") and
r.es_column.find("=")==-1 and
r.es_column.find(" ")==-1
)
with Timer("upserting {{num}} columns", {"num": len(abs_columns)}, debug=DEBUG):
def add_column(c, query_path):
c.last_updated = Date.now()
c.table = join_field([c.es_index]+split_field(query_path[0]))
with self.meta.columns.locker:
self._upsert_column(c)
for alias in meta.aliases:
c = copy(c)
c.table = join_field([alias]+split_field(query_path[0]))
self._upsert_column(c)
# LIST OF EVERY NESTED PATH
query_paths = [[c.es_column] for c in abs_columns if c.type == "nested"]
for a, b in itertools.product(query_paths, query_paths):
aa = a[0]
bb = b[0]
if aa and bb.startswith(aa):
for i, b_prefix in enumerate(b):
if len(b_prefix) > len(aa):
continue
if aa == b_prefix:
break # SPLIT ALREADY FOUND
b.insert(i, aa)
break
for q in query_paths:
q.append(".")
query_paths.append(ROOT_PATH)
# ADD RELATIVE COLUMNS
for abs_column in abs_columns:
full_path = abs_column.nested_path
abs_depth = len(full_path)-1
abs_parent = full_path[1] if abs_depth else ""
for query_path in query_paths:
rel_depth = len(query_path)-1
rel_parent = query_path[0]
rel_column = copy(abs_column)
rel_column.relative = True
add_column(copy(abs_column), query_path)
if rel_parent == ".":
add_column(rel_column, query_path)
elif abs_column.es_column.startswith(rel_parent+"."):
rel_column.name = abs_column.es_column[len(rel_parent)+1:]
add_column(rel_column, query_path)
elif abs_column.es_column == rel_parent:
rel_column.name = "."
add_column(rel_column, query_path)
elif not abs_parent:
# THIS RELATIVE NAME (..o) ALSO NEEDS A RELATIVE NAME (o)
# AND THEN REMOVE THE SHADOWED
rel_column.name = "." + ("." * (rel_depth - abs_depth)) + abs_column.es_column
add_column(rel_column, query_path)
elif rel_parent.startswith(abs_parent+"."):
rel_column.name = "." + ("." * (rel_depth - abs_depth)) + abs_column.es_column
add_column(rel_column, query_path)
elif rel_parent != abs_parent:
# SIBLING NESTED PATHS ARE INVISIBLE
pass
else:
Log.error("logic error")
def query(self, _query):
return self.meta.columns.query(QueryOp(set_default(
{
"from": self.meta.columns,
"sort": ["table", "name"]
},
_query.as_dict()
)))
def get_columns(self, table_name, column_name=None, force=False):
"""
RETURN METADATA COLUMNS
"""
try:
# LAST TIME WE GOT INFO FOR THIS TABLE
short_name = join_field(split_field(table_name)[0:1])
table = self.get_table(short_name)[0]
if not table:
table = Table(
name=short_name,
url=None,
query_path=None,
timestamp=Date.now()
)
with self.meta.tables.locker:
self.meta.tables.add(table)
self._get_columns(table=short_name)
elif force or table.timestamp == None or table.timestamp < Date.now() - MAX_COLUMN_METADATA_AGE:
table.timestamp = Date.now()
self._get_columns(table=short_name)
with self.meta.columns.locker:
columns = self.meta.columns.find(table_name, column_name)
if columns:
columns = jx.sort(columns, "name")
# AT LEAST WAIT FOR THE COLUMNS TO UPDATE
while len(self.todo) and not all(columns.get("last_updated")):
Log.note("waiting for columns to update {{columns|json}}", columns=[c.table+"."+c.es_column for c in columns if not c.last_updated])
Thread.sleep(seconds=1)
return columns
except Exception, e:
Log.error("Not expected", cause=e)
if column_name:
Log.error("no columns matching {{table}}.{{column}}", table=table_name, column=column_name)
else:
self._get_columns(table=table_name)
Log.error("no columns for {{table}}?!", table=table_name)
class FromESMetadata(Schema):
"""
QUERY THE METADATA
"""
def __new__(cls, *args, **kwargs):
global singlton
if singlton:
return singlton
else:
singlton = object.__new__(cls)
return singlton
@use_settings
def __init__(self,
host,
index,
alias=None,
name=None,
port=9200,
settings=None):
global _elasticsearch
if hasattr(self, "settings"):
return
from pyLibrary.queries.containers.list_usingPythonList import ListContainer
from pyLibrary.env import elasticsearch as _elasticsearch
self.settings = settings
self.default_name = coalesce(name, alias, index)
self.default_es = _elasticsearch.Cluster(settings=settings)
self.todo = Queue("refresh metadata", max=100000, unique=True)
self.es_metadata = Null
self.last_es_metadata = Date.now() - OLD_METADATA
self.meta = Dict()
table_columns = metadata_tables()
column_columns = metadata_columns()
self.meta.tables = ListContainer(
"meta.tables", [], wrap({c.name: c
for c in table_columns}))
self.meta.columns = ColumnList()
self.meta.columns.insert(column_columns)
self.meta.columns.insert(table_columns)
# TODO: fix monitor so it does not bring down ES
if ENABLE_META_SCAN:
self.worker = Thread.run("refresh metadata", self.monitor)
else:
self.worker = Thread.run("refresh metadata", self.not_monitor)
return
@property
def query_path(self):
return None
@property
def url(self):
return self.default_es.path + "/" + self.default_name.replace(".", "/")
def get_table(self, table_name):
with self.meta.tables.locker:
return wrap(
[t for t in self.meta.tables.data if t.name == table_name])
def _upsert_column(self, c):
# ASSUMING THE self.meta.columns.locker IS HAD
existing_columns = self.meta.columns.find(c.table, c.name)
if not existing_columns:
self.meta.columns.add(c)
self.todo.add(c)
if ENABLE_META_SCAN:
Log.note("todo: {{table}}::{{column}}",
table=c.table,
column=c.es_column)
# MARK meta.columns AS DIRTY TOO
cols = self.meta.columns.find("meta.columns", None)
for cc in cols:
cc.partitions = cc.cardinality = None
cc.last_updated = Date.now()
self.todo.extend(cols)
else:
canonical = existing_columns[0]
if canonical.relative and not c.relative:
return # RELATIVE COLUMNS WILL SHADOW ABSOLUTE COLUMNS
for key in Column.__slots__:
canonical[key] = c[key]
Log.note("todo: {{table}}::{{column}}",
table=canonical.table,
column=canonical.es_column)
self.todo.add(canonical)
def _get_columns(self, table=None):
# TODO: HANDLE MORE THEN ONE ES, MAP TABLE SHORT_NAME TO ES INSTANCE
meta = self.es_metadata.indices[table]
if not meta or self.last_es_metadata < Date.now() - OLD_METADATA:
self.es_metadata = self.default_es.get_metadata(force=True)
meta = self.es_metadata.indices[table]
for _, properties in meta.mappings.items():
self._parse_properties(meta.index, properties, meta)
def _parse_properties(self, abs_index, properties, meta):
abs_columns = _elasticsearch.parse_properties(abs_index, None,
properties.properties)
abs_columns = abs_columns.filter( # TODO: REMOVE WHEN jobs PROPERTY EXPLOSION IS CONTAINED
lambda r: not r.es_column.startswith("other.") and not r.es_column.
startswith("previous_values.cf_") and not r.es_index.startswith(
"debug") and r.es_column.find("=") == -1 and r.es_column.find(
" ") == -1)
with Timer("upserting {{num}} columns", {"num": len(abs_columns)},
debug=DEBUG):
def add_column(c, query_path):
c.last_updated = Date.now()
c.table = join_field([c.es_index] + split_field(query_path[0]))
with self.meta.columns.locker:
self._upsert_column(c)
for alias in meta.aliases:
c = copy(c)
c.table = join_field([alias] +
split_field(query_path[0]))
self._upsert_column(c)
# LIST OF EVERY NESTED PATH
query_paths = [[c.es_column] for c in abs_columns
if c.type == "nested"]
for a, b in itertools.product(query_paths, query_paths):
aa = a[0]
bb = b[0]
if aa and bb.startswith(aa):
for i, b_prefix in enumerate(b):
if len(b_prefix) > len(aa):
continue
if aa == b_prefix:
break # SPLIT ALREADY FOUND
b.insert(i, aa)
break
for q in query_paths:
q.append(".")
query_paths.append(ROOT_PATH)
# ADD RELATIVE COLUMNS
for abs_column in abs_columns:
full_path = abs_column.nested_path
abs_depth = len(full_path) - 1
abs_parent = full_path[1] if abs_depth else ""
for query_path in query_paths:
rel_depth = len(query_path) - 1
rel_parent = query_path[0]
rel_column = copy(abs_column)
rel_column.relative = True
add_column(copy(abs_column), query_path)
if rel_parent == ".":
add_column(rel_column, query_path)
elif abs_column.es_column.startswith(rel_parent + "."):
rel_column.name = abs_column.es_column[len(rel_parent
) + 1:]
add_column(rel_column, query_path)
elif abs_column.es_column == rel_parent:
rel_column.name = "."
add_column(rel_column, query_path)
elif not abs_parent:
# THIS RELATIVE NAME (..o) ALSO NEEDS A RELATIVE NAME (o)
# AND THEN REMOVE THE SHADOWED
rel_column.name = "." + (
"." *
(rel_depth - abs_depth)) + abs_column.es_column
add_column(rel_column, query_path)
elif rel_parent.startswith(abs_parent + "."):
rel_column.name = "." + (
"." *
(rel_depth - abs_depth)) + abs_column.es_column
add_column(rel_column, query_path)
elif rel_parent != abs_parent:
# SIBLING NESTED PATHS ARE INVISIBLE
pass
else:
Log.error("logic error")
def query(self, _query):
return self.meta.columns.query(
QueryOp(
set_default(
{
"from": self.meta.columns,
"sort": ["table", "name"]
}, _query.as_dict())))
def get_columns(self, table_name, column_name=None, force=False):
"""
RETURN METADATA COLUMNS
"""
try:
# LAST TIME WE GOT INFO FOR THIS TABLE
short_name = join_field(split_field(table_name)[0:1])
table = self.get_table(short_name)[0]
if not table:
table = Table(name=short_name,
url=None,
query_path=None,
timestamp=Date.now())
with self.meta.tables.locker:
self.meta.tables.add(table)
self._get_columns(table=short_name)
elif force or table.timestamp == None or table.timestamp < Date.now(
) - MAX_COLUMN_METADATA_AGE:
table.timestamp = Date.now()
self._get_columns(table=short_name)
with self.meta.columns.locker:
columns = self.meta.columns.find(table_name, column_name)
if columns:
columns = jx.sort(columns, "name")
# AT LEAST WAIT FOR THE COLUMNS TO UPDATE
while len(self.todo) and not all(columns.get("last_updated")):
Log.note("waiting for columns to update {{columns|json}}",
columns=[
c.table + "." + c.es_column for c in columns
if not c.last_updated
])
Thread.sleep(seconds=1)
return columns
except Exception, e:
Log.error("Not expected", cause=e)
if column_name:
Log.error("no columns matching {{table}}.{{column}}",
table=table_name,
column=column_name)
else:
self._get_columns(table=table_name)
Log.error("no columns for {{table}}?!", table=table_name)
class FromESMetadata(object):
"""
QUERY THE METADATA
"""
def __new__(cls, *args, **kwargs):
global singlton
if singlton:
return singlton
else:
singlton = object.__new__(cls)
return singlton
@use_settings
def __init__(self, host, index, alias=None, name=None, port=9200, settings=None):
global _elasticsearch
if hasattr(self, "settings"):
return
from pyLibrary.queries.containers.lists import ListContainer
from pyLibrary.env import elasticsearch as _elasticsearch
self.settings = settings
self.default_name = coalesce(name, alias, index)
self.default_es = _elasticsearch.Cluster(settings=settings)
self.todo = Queue("refresh metadata", max=100000, unique=True)
table_columns = metadata_tables()
column_columns = metadata_columns()
self.tables = ListContainer("meta.tables", [], wrap({c.name: c for c in table_columns}))
self.columns = ListContainer("meta.columns", [], wrap({c.name: c for c in column_columns}))
self.columns.insert(column_columns)
self.columns.insert(table_columns)
# TODO: fix monitor so it does not bring down ES
if ENABLE_META_SCAN:
self.worker = Thread.run("refresh metadata", self.monitor)
else:
self.worker = Thread.run("refresh metadata", self.not_monitor)
return
@property
def query_path(self):
return None
@property
def url(self):
return self.default_es.path + "/" + self.default_name.replace(".", "/")
def get_table(self, table_name):
with self.tables.locker:
return self.tables.query({"where": {"eq": {"name": table_name}}})
def upsert_column(self, c):
existing_columns = filter(lambda r: r.table == c.table and r.abs_name == c.abs_name, self.columns.data)
if not existing_columns:
self.columns.add(c)
cols = filter(lambda r: r.table == "meta.columns", self.columns.data)
for cc in cols:
cc.partitions = cc.cardinality = cc.last_updated = None
self.todo.add(c)
self.todo.extend(cols)
else:
set_default(existing_columns[0], c)
self.todo.add(existing_columns[0])
# TEST CONSISTENCY
for c, d in product(list(self.todo.queue), list(self.todo.queue)):
if c.abs_name==d.abs_name and c.table==d.table and c!=d:
Log.error("")
def _get_columns(self, table=None):
# TODO: HANDLE MORE THEN ONE ES, MAP TABLE SHORT_NAME TO ES INSTANCE
alias_done = set()
index = split_field(table)[0]
query_path = split_field(table)[1:]
metadata = self.default_es.get_metadata(index=index)
for index, meta in qb.sort(metadata.indices.items(), {"value": 0, "sort": -1}):
for _, properties in meta.mappings.items():
columns = _elasticsearch.parse_properties(index, None, properties.properties)
columns = columns.filter(lambda r: not r.abs_name.startswith("other.") and not r.abs_name.startswith("previous_values.cf_")) # TODO: REMOVE WHEN jobs PROPERTY EXPLOSION IS CONTAINED
with Timer("upserting {{num}} columns", {"num": len(columns)}, debug=DEBUG):
with self.columns.locker:
for c in columns:
# ABSOLUTE
c.table = join_field([index]+query_path)
self.upsert_column(c)
for alias in meta.aliases:
# ONLY THE LATEST ALIAS IS CHOSEN TO GET COLUMNS
if alias in alias_done:
continue
alias_done.add(alias)
c = copy(c)
c.table = join_field([alias]+query_path)
self.upsert_column(c)
def query(self, _query):
return self.columns.query(Query(set_default(
{
"from": self.columns,
"sort": ["table", "name"]
},
_query.as_dict()
)))
def get_columns(self, table):
"""
RETURN METADATA COLUMNS
"""
with self.columns.locker:
columns = qb.sort(filter(lambda r: r.table == table, self.columns.data), "name")
if columns:
return columns
self._get_columns(table=table)
with self.columns.locker:
columns = qb.sort(filter(lambda r: r.table == table, self.columns.data), "name")
if columns:
return columns
# self._get_columns(table=table)
Log.error("no columns for {{table}}", table=table)
def _update_cardinality(self, c):
"""
QUERY ES TO FIND CARDINALITY AND PARTITIONS FOR A SIMPLE COLUMN
"""
if c.type in ["object", "nested"]:
Log.error("not supported")
try:
if c.table == "meta.columns":
with self.columns.locker:
partitions = qb.sort([g[c.abs_name] for g, _ in qb.groupby(self.columns, c.abs_name) if g[c.abs_name] != None])
self.columns.update({
"set": {
"partitions": partitions,
"count": len(self.columns),
"cardinality": len(partitions),
"last_updated": Date.now()
},
"where": {"eq": {"table": c.table, "abs_name": c.abs_name}}
})
return
if c.table == "meta.tables":
with self.columns.locker:
partitions = qb.sort([g[c.abs_name] for g, _ in qb.groupby(self.tables, c.abs_name) if g[c.abs_name] != None])
self.columns.update({
"set": {
"partitions": partitions,
"count": len(self.tables),
"cardinality": len(partitions),
"last_updated": Date.now()
},
"where": {"eq": {"table": c.table, "name": c.name}}
})
return
es_index = c.table.split(".")[0]
result = self.default_es.post("/"+es_index+"/_search", data={
"aggs": {c.name: _counting_query(c)},
"size": 0
})
r = result.aggregations.values()[0]
count = result.hits.total
cardinality = coalesce(r.value, r._nested.value)
if cardinality == None:
Log.error("logic error")
query = Dict(size=0)
if c.type in ["object", "nested"]:
Log.note("{{field}} has {{num}} parts", field=c.name, num=cardinality)
with self.columns.locker:
self.columns.update({
"set": {
"count": count,
"cardinality": cardinality,
"last_updated": Date.now()
},
"clear": ["partitions"],
"where": {"eq": {"table": c.table, "name": c.name}}
})
return
elif cardinality > 1000 or (count >= 30 and cardinality == count) or (count >= 1000 and cardinality / count > 0.99):
Log.note("{{field}} has {{num}} parts", field=c.name, num=cardinality)
with self.columns.locker:
self.columns.update({
"set": {
"count": count,
"cardinality": cardinality,
"last_updated": Date.now()
},
"clear": ["partitions"],
"where": {"eq": {"table": c.table, "name": c.name}}
})
return
elif c.type in _elasticsearch.ES_NUMERIC_TYPES and cardinality > 30:
Log.note("{{field}} has {{num}} parts", field=c.name, num=cardinality)
with self.columns.locker:
self.columns.update({
"set": {
"count": count,
"cardinality": cardinality,
"last_updated": Date.now()
},
"clear": ["partitions"],
"where": {"eq": {"table": c.table, "name": c.name}}
})
return
elif c.nested_path:
query.aggs[literal_field(c.name)] = {
"nested": {"path": listwrap(c.nested_path)[0]},
"aggs": {"_nested": {"terms": {"field": c.abs_name, "size": 0}}}
}
else:
query.aggs[literal_field(c.name)] = {"terms": {"field": c.abs_name, "size": 0}}
result = self.default_es.post("/"+es_index+"/_search", data=query)
aggs = result.aggregations.values()[0]
if aggs._nested:
parts = qb.sort(aggs._nested.buckets.key)
else:
parts = qb.sort(aggs.buckets.key)
Log.note("{{field}} has {{parts}}", field=c.name, parts=parts)
with self.columns.locker:
self.columns.update({
"set": {
"count": count,
"cardinality": cardinality,
"partitions": parts,
"last_updated": Date.now()
},
"where": {"eq": {"table": c.table, "abs_name": c.abs_name}}
})
except Exception, e:
if "IndexMissingException" in e and c.table.startswith("testing"):
Log.alert("{{col.table}} does not exist", col=c)
else:
self.columns.update({
"set": {
"last_updated": Date.now()
},
"clear":[
"count",
"cardinality",
"partitions",
],
"where": {"eq": {"table": c.table, "abs_name": c.abs_name}}
})
Log.warning("Could not get {{col.table}}.{{col.abs_name}} info", col=c, cause=e)
