def _es_terms2(es, mvel, query):
"""
WE ASSUME THERE ARE JUST TWO EDGES, AND EACH HAS A SIMPLE value
"""
# REQUEST VALUES IN FIRST DIMENSION
q1 = query.copy()
q1.edges = query.edges[0:1:]
values1 = es_terms(es, mvel, q1).edges[0].domain.partitions.value
select = listwrap(query.select)
FromES = build_es_query(query)
for s in select:
for i, v in enumerate(values1):
FromES.facets[s.name + "," + str(i)] = {
"terms": {
"field": query.edges[1].value,
"size": coalesce(query.limit, 200000)
},
"facet_filter": simplify_esfilter({"and": [
query.where,
{"term": {query.edges[0].value: v}}
]})
}
data = es_post(es, FromES, query.limit)
# UNION ALL TERMS FROM SECOND DIMENSION
values2 = set()
for k, f in data.facets.items():
values2.update(f.terms.term)
values2 = jx.sort(values2)
term2index = {v: i for i, v in enumerate(values2)}
query.edges[1].domain.partitions = FlatList([{"name": v, "value": v} for v in values2])
# MAKE CUBE
output = {}
dims = [len(values1), len(values2)]
for s in select:
output[s.name] = Matrix(*dims)
# FILL CUBE
# EXPECTING ONLY SELECT CLAUSE FACETS
for facetName, facet in data.facets.items():
coord = facetName.split(",")
s = [s for s in select if s.name == coord[0]][0]
i1 = int(coord[1])
for term in facet.terms:
i2 = term2index[term.term]
output[s.name][(i1, i2)] = term[aggregates[s.aggregate]]
cube = Cube(query.select, query.edges, output)
cube.query = query
return cube
def _es_terms2(es, mvel, query):
"""
WE ASSUME THERE ARE JUST TWO EDGES, AND EACH HAS A SIMPLE value
"""
# REQUEST VALUES IN FIRST DIMENSION
q1 = query.copy()
q1.edges = query.edges[0:1:]
values1 = es_terms(es, mvel, q1).edges[0].domain.partitions.value
select = listwrap(query.select)
FromES = build_es_query(query)
for s in select:
for i, v in enumerate(values1):
FromES.facets[s.name + "," + str(i)] = {
"terms": {
"field": query.edges[1].value,
"size": coalesce(query.limit, 200000)
},
"facet_filter": simplify_esfilter({"and": [
query.where,
{"term": {query.edges[0].value: v}}
]})
}
data = es_post(es, FromES, query.limit)
# UNION ALL TERMS FROM SECOND DIMENSION
values2 = set()
for k, f in data.facets.items():
values2.update(f.terms.term)
values2 = jx.sort(values2)
term2index = {v: i for i, v in enumerate(values2)}
query.edges[1].domain.partitions = FlatList([{"name": v, "value": v} for v in values2])
# MAKE CUBE
output = {}
dims = [len(values1), len(values2)]
for s in select:
output[s.name] = Matrix(*dims)
# FILL CUBE
# EXPECTING ONLY SELECT CLAUSE FACETS
for facetName, facet in data.facets.items():
coord = facetName.split(",")
s = [s for s in select if s.name == coord[0]][0]
i1 = int(coord[1])
for term in facet.terms:
i2 = term2index[term.term]
output[s.name][(i1, i2)] = term[aggregates[s.aggregate]]
cube = Cube(query.select, query.edges, output)
cube.query = query
return cube
def es_terms(es, mvel, query):
"""
RETURN LIST OF ALL EDGE QUERIES
EVERY FACET IS NAMED <select.name>, <c1>, ... <cN> WHERE <ci> ARE THE ELEMENT COORDINATES
WE TRY TO PACK DIMENSIONS INTO THE TERMS TO MINIMIZE THE CROSS-PRODUCT EXPLOSION
"""
if len(query.edges) == 2:
return _es_terms2(es, mvel, query)
select = listwrap(query.select)
FromES = build_es_query(query)
packed_term = compileEdges2Term(mvel, query.edges, wrap([]))
for s in select:
FromES.facets[s.name] = {
"terms": {
"field": packed_term.field,
"script_field": packed_term.expression,
"size": coalesce(query.limit, 200000)
},
"facet_filter": simplify_esfilter(query.where)
}
term2Parts = packed_term.term2parts
data = es_post(es, FromES, query.limit)
# GETTING ALL PARTS WILL EXPAND THE EDGES' DOMAINS
# BUT HOW TO UNPACK IT FROM THE term FASTER IS UNKNOWN
for k, f in data.facets.items():
for t in f.terms:
term2Parts(t.term)
# NUMBER ALL EDGES FOR jx INDEXING
for f, e in enumerate(query.edges):
e.index = f
if e.domain.type in ["uid", "default"]:
# e.domain.partitions = jx.sort(e.domain.partitions, "value")
for p, part in enumerate(e.domain.partitions):
part.dataIndex = p
e.domain.NULL.dataIndex = len(e.domain.partitions)
# MAKE CUBE
output = {}
dims = [
len(e.domain.partitions) + (1 if e.allowNulls else 0)
for e in query.edges
]
for s in select:
output[s.name] = Matrix(*dims)
# FILL CUBE
# EXPECTING ONLY SELECT CLAUSE FACETS
for facetName, facet in data.facets.items():
for term in facet.terms:
term_coord = term2Parts(term.term).dataIndex
for s in select:
try:
output[s.name][term_coord] = term[aggregates[s.aggregate]]
except Exception as e:
# USUALLY CAUSED BY output[s.name] NOT BEING BIG ENOUGH TO HANDLE NULL COUNTS
pass
cube = Cube(query.select, query.edges, output)
cube.query = query
return cube
def es_terms(es, mvel, query):
"""
RETURN LIST OF ALL EDGE QUERIES
EVERY FACET IS NAMED <select.name>, <c1>, ... <cN> WHERE <ci> ARE THE ELEMENT COORDINATES
WE TRY TO PACK DIMENSIONS INTO THE TERMS TO MINIMIZE THE CROSS-PRODUCT EXPLOSION
"""
if len(query.edges) == 2:
return _es_terms2(es, mvel, query)
select = listwrap(query.select)
FromES = build_es_query(query)
packed_term = compileEdges2Term(mvel, query.edges, wrap([]))
for s in select:
FromES.facets[s.name] = {
"terms": {
"field": packed_term.field,
"script_field": packed_term.expression,
"size": coalesce(query.limit, 200000)
},
"facet_filter": simplify_esfilter(query.where)
}
term2Parts = packed_term.term2parts
data = es_post(es, FromES, query.limit)
# GETTING ALL PARTS WILL EXPAND THE EDGES' DOMAINS
# BUT HOW TO UNPACK IT FROM THE term FASTER IS UNKNOWN
for k, f in data.facets.items():
for t in f.terms:
term2Parts(t.term)
# NUMBER ALL EDGES FOR jx INDEXING
for f, e in enumerate(query.edges):
e.index = f
if e.domain.type in ["uid", "default"]:
# e.domain.partitions = jx.sort(e.domain.partitions, "value")
for p, part in enumerate(e.domain.partitions):
part.dataIndex = p
e.domain.NULL.dataIndex = len(e.domain.partitions)
# MAKE CUBE
output = {}
dims = [len(e.domain.partitions) + (1 if e.allowNulls else 0) for e in query.edges]
for s in select:
output[s.name] = Matrix(*dims)
# FILL CUBE
# EXPECTING ONLY SELECT CLAUSE FACETS
for facetName, facet in data.facets.items():
for term in facet.terms:
term_coord = term2Parts(term.term).dataIndex
for s in select:
try:
output[s.name][term_coord] = term[aggregates[s.aggregate]]
except Exception as e:
# USUALLY CAUSED BY output[s.name] NOT BEING BIG ENOUGH TO HANDLE NULL COUNTS
pass
cube = Cube(query.select, query.edges, output)
cube.query = query
return cube