def append_query(self, es_query, start):
self.start = start
parts = self.edge.domain.partitions
filters = []
notty = []
for p in parts:
filters.append(AndOp("and", [p.where]+notty).to_esfilter())
notty.append(NotOp("not", p.where))
missing_filter = None
if self.edge.allowNulls: # TODO: Use Expression.missing().esfilter() TO GET OPTIMIZED FILTER
missing_filter = set_default(
{"filter": AndOp("and", notty).to_esfilter()},
es_query
)
return wrap({"aggs": {
"_match": set_default(
{"filters": {"filters": filters}},
es_query
),
"_missing": missing_filter
}})
def append_query(self, es_query, start):
self.start = start
edge = self.edge
range = edge.range
domain = edge.domain
aggs = {}
for i, p in enumerate(domain.partitions):
filter_ = AndOp("and", [
InequalityOp("lte", [range.min, Literal("literal", self.to_float(p.min))]),
InequalityOp("gt", [range.max, Literal("literal", self.to_float(p.min))])
])
aggs["_join_" + unicode(i)] = set_default(
{"filter": filter_.to_esfilter()},
es_query
)
return wrap({"aggs": aggs})
def es_aggsop(es, frum, query):
select = wrap([s.copy() for s in listwrap(query.select)])
es_column_map = {c.name: unwraplist(c.es_column) for c in frum.schema.all_columns}
es_query = Dict()
new_select = Dict() #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 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, map_=es_column_map)
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 = Dict(
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")
for d in 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 = Dict(
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, 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 es_deepop(es, query):
schema = query.frum.schema
columns = schema.columns
query_path = schema.query_path
map_to_local = {k: get_pull(c[0]) for k, c in schema.lookup.items()}
# TODO: FIX THE GREAT SADNESS CAUSED BY EXECUTING post_expressions
# THE EXPRESSIONS SHOULD BE PUSHED TO THE CONTAINER: ES ALLOWS
# {"inner_hit":{"script_fields":[{"script":""}...]}}, BUT THEN YOU
# LOOSE "_source" BUT GAIN "fields", FORCING ALL FIELDS TO BE EXPLICIT
post_expressions = {}
es_query, es_filters = es14.util.es_query_template(query.frum.name)
# SPLIT WHERE CLAUSE BY DEPTH
wheres = split_expression_by_depth(query.where, schema)
for i, f in enumerate(es_filters):
# PROBLEM IS {"match_all": {}} DOES NOT SURVIVE set_default()
for k, v in unwrap(simplify_esfilter(AndOp("and", wheres[i]).to_esfilter())).items():
f[k] = v
if not wheres[1]:
more_filter = {
"and": [
simplify_esfilter(AndOp("and", wheres[0]).to_esfilter()),
{"not": {
"nested": {
"path": query_path,
"filter": {
"match_all": {}
}
}
}}
]
}
else:
more_filter = None
es_query.size = coalesce(query.limit, queries.query.DEFAULT_LIMIT)
es_query.sort = jx_sort_to_es_sort(query.sort)
es_query.fields = []
is_list = isinstance(query.select, list)
new_select = FlatList()
i = 0
for s in listwrap(query.select):
if isinstance(s.value, LeavesOp):
if isinstance(s.value.term, Variable):
if s.value.term.var == ".":
# IF THERE IS A *, THEN INSERT THE EXTRA COLUMNS
for c in columns:
if c.type not in STRUCT and c.es_column != "_id":
if c.nested_path[0] == ".":
es_query.fields += [c.es_column]
new_select.append({
"name": c.names[query_path],
"pull": get_pull(c),
"nested_path": c.nested_path[0],
"put": {"name": literal_field(c.names[query_path]), "index": i, "child": "."}
})
i += 1
# REMOVE DOTS IN PREFIX IF NAME NOT AMBIGUOUS
col_names = set(c.names[query_path] for c in columns)
for n in new_select:
if n.name.startswith("..") and n.name.lstrip(".") not in col_names:
n.name = n.name.lstrip(".")
n.put.name = literal_field(n.name)
col_names.add(n.name)
else:
prefix = schema[s.value.term.var][0].names["."] + "."
prefix_length = len(prefix)
for c in columns:
cname = c.names["."]
if cname.startswith(prefix) and c.type not in STRUCT:
pull = get_pull(c)
if c.nested_path[0] == ".":
es_query.fields += [c.es_column]
new_select.append({
"name": s.name + "." + cname[prefix_length:],
"pull": pull,
"nested_path": c.nested_path[0],
"put": {
"name": s.name + "." + literal_field(cname[prefix_length:]),
"index": i,
"child": "."
}
})
i += 1
elif isinstance(s.value, Variable):
if s.value.var == ".":
for c in columns:
if c.type not in STRUCT and c.es_column != "_id":
if len(c.nested_path) == 1:
es_query.fields += [c.es_column]
new_select.append({
"name": c.name,
"pull": get_pull(c),
"nested_path": c.nested_path[0],
"put": {"name": ".", "index": i, "child": c.es_column}
})
i += 1
elif s.value.var == "_id":
new_select.append({
"name": s.name,
"value": s.value.var,
"pull": "_id",
"put": {"name": s.name, "index": i, "child": "."}
})
i += 1
else:
prefix = schema[s.value.var][0]
if not prefix:
net_columns = []
else:
parent = prefix.es_column+"."
prefix_length = len(parent)
net_columns = [c for c in columns if c.es_column.startswith(parent) and c.type not in STRUCT]
if not net_columns:
pull = get_pull(prefix)
if len(prefix.nested_path) == 1:
es_query.fields += [prefix.es_column]
new_select.append({
"name": s.name,
"pull": pull,
"nested_path": prefix.nested_path[0],
"put": {"name": s.name, "index": i, "child": "."}
})
else:
done = set()
for n in net_columns:
# THE COLUMNS CAN HAVE DUPLICATE REFERNCES TO THE SAME ES_COLUMN
if n.es_column in done:
continue
done.add(n.es_column)
pull = get_pull(n)
if len(n.nested_path) == 1:
es_query.fields += [n.es_column]
new_select.append({
"name": s.name,
"pull": pull,
"nested_path": n.nested_path[0],
"put": {"name": s.name, "index": i, "child": n.es_column[prefix_length:]}
})
i += 1
else:
expr = s.value
for v in expr.vars():
for c in schema[v]:
if c.nested_path[0] == ".":
es_query.fields += [c.es_column]
# else:
# Log.error("deep field not expected")
pull = EXPRESSION_PREFIX + s.name
post_expressions[pull] = compile_expression(expr.map(map_to_local).to_python())
new_select.append({
"name": s.name if is_list else ".",
"pull": pull,
"value": expr.__data__(),
"put": {"name": s.name, "index": i, "child": "."}
})
i += 1
# <COMPLICATED> ES needs two calls to get all documents
more = []
def get_more(please_stop):
more.append(es09.util.post(
es,
Data(
filter=more_filter,
fields=es_query.fields
),
query.limit
))
if more_filter:
need_more = Thread.run("get more", target=get_more)
with Timer("call to ES") as call_timer:
data = es09.util.post(es, es_query, query.limit)
# EACH A HIT IS RETURNED MULTIPLE TIMES FOR EACH INNER HIT, WITH INNER HIT INCLUDED
def inners():
for t in data.hits.hits:
for i in t.inner_hits[literal_field(query_path)].hits.hits:
t._inner = i._source
for k, e in post_expressions.items():
t[k] = e(t)
yield t
if more_filter:
Thread.join(need_more)
for t in more[0].hits.hits:
yield t
#</COMPLICATED>
try:
formatter, groupby_formatter, mime_type = format_dispatch[query.format]
output = formatter(inners(), new_select, query)
output.meta.timing.es = call_timer.duration
output.meta.content_type = mime_type
output.meta.es_query = es_query
return output
except Exception as e:
Log.error("problem formatting", e)