def is_setop(es, query):
if not any(
map(es.cluster.version.startswith,
["1.4.", "1.5.", "1.6.", "1.7."])):
return False
select = listwrap(query.select)
if not query.edges:
isDeep = len(split_field(
query.frum.name)) > 1 # LOOKING INTO NESTED WILL REQUIRE A SCRIPT
simpleAgg = AND([
s.aggregate in ("count", "none") for s in select
]) # CONVERTING esfilter DEFINED PARTS WILL REQUIRE SCRIPT
# NO EDGES IMPLIES SIMPLER QUERIES: EITHER A SET OPERATION, OR RETURN SINGLE AGGREGATE
if simpleAgg or isDeep:
return True
else:
isSmooth = AND(
(e.domain.type in ALGEBRAIC and e.domain.interval == "none")
for e in query.edges)
if isSmooth:
return True
return False
def _map_term_using_schema(master, path, term, schema_edges):
"""
IF THE WHERE CLAUSE REFERS TO FIELDS IN THE SCHEMA, THEN EXPAND THEM
"""
output = FlatList()
for k, v in term.items():
dimension = schema_edges[k]
if isinstance(dimension, Dimension):
domain = dimension.getDomain()
if dimension.fields:
if is_data(dimension.fields):
# EXPECTING A TUPLE
for local_field, es_field in dimension.fields.items():
local_value = v[local_field]
if local_value == None:
output.append({"missing": {"field": es_field}})
else:
output.append({"term": {es_field: local_value}})
continue
if len(dimension.fields) == 1 and is_variable_name(dimension.fields[0]):
# SIMPLE SINGLE-VALUED FIELD
if domain.getPartByKey(v) is domain.NULL:
output.append({"missing": {"field": dimension.fields[0]}})
else:
output.append({"term": {dimension.fields[0]: v}})
continue
if AND(is_variable_name(f) for f in dimension.fields):
# EXPECTING A TUPLE
if not isinstance(v, tuple):
Log.error("expecing {{name}}={{value}} to be a tuple", name= k, value= v)
for i, f in enumerate(dimension.fields):
vv = v[i]
if vv == None:
output.append({"missing": {"field": f}})
else:
output.append({"term": {f: vv}})
continue
if len(dimension.fields) == 1 and is_variable_name(dimension.fields[0]):
if domain.getPartByKey(v) is domain.NULL:
output.append({"missing": {"field": dimension.fields[0]}})
else:
output.append({"term": {dimension.fields[0]: v}})
continue
if domain.partitions:
part = domain.getPartByKey(v)
if part is domain.NULL or not part.esfilter:
Log.error("not expected to get NULL")
output.append(part.esfilter)
continue
else:
Log.error("not expected")
elif is_data(v):
sub = _map_term_using_schema(master, path + [k], v, schema_edges[k])
output.append(sub)
continue
output.append({"term": {k: v}})
return {"and": output}
def is_terms(query):
select = listwrap(query.select)
isSimple = not query.select or AND(aggregates[s.aggregate] in ("none", "count") for s in select)
if isSimple:
return True
return False
def is_fieldop(query):
# THESE SMOOTH EDGES REQUIRE ALL DATA (SETOP)
select = listwrap(query.select)
if not query.edges:
isDeep = len(split_field(
query.frum.name)) > 1 # LOOKING INTO NESTED WILL REQUIRE A SCRIPT
isSimple = AND(
s.value != None and (s.value == "*" or is_variable_name(s.value))
for s in select)
noAgg = AND(s.aggregate == "none" for s in select)
if not isDeep and isSimple and noAgg:
return True
else:
isSmooth = AND((
e.domain.type in domains.ALGEBRAIC and e.domain.interval == "none")
for e in query.edges)
if isSmooth:
return True
return False
def es_aggop(es, mvel, query):
select = listwrap(query.select)
FromES = build_es_query(query)
isSimple = AND(aggregates[s.aggregate] == "count" for s in select)
if isSimple:
return es_countop(es, query) # SIMPLE, USE TERMS FACET INSTEAD
value2facet = dict() # ONLY ONE FACET NEEDED PER
name2facet = dict() # MAP name TO FACET WITH STATS
for s in select:
if s.value not in value2facet:
if isinstance(s.value, Variable):
unwrap(FromES.facets)[s.name] = {
"statistical": {
"field": s.value.var
},
"facet_filter":
simplify_esfilter(query.where.to_esfilter())
}
else:
unwrap(FromES.facets)[s.name] = {
"statistical": {
"script": jx_expression_to_function(s.value)
},
"facet_filter": simplify_esfilter(query.where)
}
value2facet[s.value] = s.name
name2facet[s.name] = value2facet[s.value]
data = es09.util.post(es, FromES, query.limit)
matricies = {
s.name: Matrix(value=fix_es_stats(data.facets[literal_field(s.name)])[
aggregates[s.aggregate]])
for s in select
}
cube = Cube(query.select, [], matricies)
cube.frum = query
return cube
