def format_cube(decoders, aggs, start, query, select):
# decoders = sorted(decoders, key=lambda d: -d.edge.dim) # REVERSE DECODER ORDER, BECAUSE ES QUERY WAS BUILT IN REVERSE ORDER
new_edges = count_dim(aggs, decoders)
dims = []
for e in new_edges:
if isinstance(e.value, TupleOp):
e.allowNulls = False
extra = 0 if e.allowNulls is False else 1
dims.append(len(e.domain.partitions) + extra)
dims = tuple(dims)
matricies = [(s, Matrix(dims=dims, zeros=s.default)) for s in select]
for row, coord, agg in aggs_iterator(aggs, decoders):
for s, m in matricies:
try:
v = _pull(s, agg)
m[coord] = v
except Exception as e:
Log.error("", e)
cube = Cube(
query.select,
sorted(new_edges, key=lambda e: e.dim), # ENSURE EDGES ARE IN SAME ORDER AS QUERY
{s.name: m for s, m in matricies}
)
cube.frum = query
return cube
def format_cube(decoders, aggs, start, query, select):
new_edges = count_dim(aggs, decoders)
dims = []
for e in new_edges:
if isinstance(e.value, TupleOp):
e.allowNulls = False
if e.allowNulls is False:
extra = 0
else:
extra = 1
dims.append(len(e.domain.partitions)+extra)
dims = tuple(dims)
matricies = [(s, Matrix(dims=dims, zeros=s.default)) for s in select]
for row, coord, agg in aggs_iterator(aggs, decoders):
for s, m in matricies:
try:
v = _pull(s, agg)
m[coord] = v
except Exception as e:
Log.error("", e)
cube = Cube(query.select, new_edges, {s.name: m for s, m in matricies})
cube.frum = query
return cube
def es_countop(es, mvel, query):
"""
RETURN SINGLE COUNT
"""
select = listwrap(query.select)
FromES = build_es_query(query)
for s in select:
if is_keyword(s.value):
FromES.facets[s.name] = {
"terms": {
"field": s.value,
"size": query.limit,
},
"facet_filter":{"exists":{"field":s.value}}
}
else:
# COMPLICATED value IS PROBABLY A SCRIPT, USE IT
FromES.facets[s.name] = {
"terms": {
"script_field": es09.expressions.compile_expression(s.value, query),
"size": 200000
}
}
data = es09.util.post(es, FromES, query.limit)
matricies = {}
for s in select:
matricies[s.name] = Matrix(value=data.hits.facets[s.name].total)
cube = Cube(query.select, query.edges, matricies)
cube.frum = query
return cube
def format_cube(decoders, aggs, start, query, select):
# decoders = sorted(decoders, key=lambda d: -d.edge.dim) # REVERSE DECODER ORDER, BECAUSE ES QUERY WAS BUILT IN REVERSE ORDER
new_edges = count_dim(aggs, decoders)
dims = []
for e in new_edges:
if isinstance(e.value, TupleOp):
e.allowNulls = False
extra = 0 if e.allowNulls is False else 1
dims.append(len(e.domain.partitions) + extra)
dims = tuple(dims)
matricies = [(s, Matrix(dims=dims, zeros=s.default)) for s in select]
for row, coord, agg in aggs_iterator(aggs, decoders):
for s, m in matricies:
try:
v = _pull(s, agg)
m[coord] = v
except Exception as e:
Log.error("", e)
cube = Cube(
query.select,
sorted(new_edges,
key=lambda e: e.dim), # ENSURE EDGES ARE IN SAME ORDER AS QUERY
{s.name: m
for s, m in matricies})
cube.frum = query
return cube
def es_countop(es, mvel, query):
"""
RETURN SINGLE COUNT
"""
select = listwrap(query.select)
FromES = build_es_query(query)
for s in select:
if is_keyword(s.value):
FromES.facets[s.name] = {
"terms": {
"field": s.value,
"size": query.limit,
},
"facet_filter":{"exists":{"field":s.value}}
}
else:
# COMPLICATED value IS PROBABLY A SCRIPT, USE IT
FromES.facets[s.name] = {
"terms": {
"script_field": es09.expressions.compile_expression(s.value, query),
"size": 200000
}
}
data = es09.util.post(es, FromES, query.limit)
matricies = {}
for s in select:
matricies[s.name] = Matrix(value=data.hits.facets[s.name].total)
cube = Cube(query.select, query.edges, matricies)
cube.frum = query
return cube
def es_fieldop(es, query):
FromES = es09.util.build_es_query(query)
select = listwrap(query.select)
FromES.query = {
"filtered": {
"query": {
"match_all": {}
},
"filter":
simplify_esfilter(jx_expression(query.where).to_esfilter())
}
}
FromES.size = coalesce(query.limit, 200000)
FromES.fields = FlatList()
for s in select.value:
if s == "*":
FromES.fields = None
elif isinstance(s, list):
FromES.fields.extend(s)
elif isinstance(s, Mapping):
FromES.fields.extend(s.values())
else:
FromES.fields.append(s)
FromES.sort = [{
s.field: "asc" if s.sort >= 0 else "desc"
} for s in query.sort]
data = es09.util.post(es, FromES, query.limit)
T = data.hits.hits
matricies = {}
for s in select:
if s.value == "*":
matricies[s.name] = Matrix.wrap([t._source for t in T])
elif isinstance(s.value, Mapping):
# for k, v in s.value.items():
# matricies[join_field(split_field(s.name)+[k])] = Matrix.wrap([unwrap(t.fields)[v] for t in T])
matricies[s.name] = Matrix.wrap([{
k: unwrap(t.fields).get(v, None)
for k, v in s.value.items()
} for t in T])
elif isinstance(s.value, list):
matricies[s.name] = Matrix.wrap([
tuple(unwrap(t.fields).get(ss, None) for ss in s.value)
for t in T
])
elif not s.value:
matricies[s.name] = Matrix.wrap(
[unwrap(t.fields).get(s.value, None) for t in T])
else:
try:
matricies[s.name] = Matrix.wrap(
[unwrap(t.fields).get(s.value, None) for t in T])
except Exception as e:
Log.error("", e)
cube = Cube(query.select, query.edges, matricies, frum=query)
cube.frum = query
return cube
def format_cube_from_aggop(decoders, aggs, start, query, select):
agg = drill(aggs)
matricies = [(s, Matrix(dims=[], zeros=s.default)) for s in select]
for s, m in matricies:
m[tuple()] = _pull(s, agg)
cube = Cube(query.select, [], {s.name: m for s, m in matricies})
cube.frum = query
return cube
def format_cube_from_aggop(decoders, aggs, start, query, select):
agg = drill(aggs)
matricies = [(s, Matrix(dims=[], zeros=s.default)) for s in select]
for s, m in matricies:
m[tuple()] = _pull(s, agg)
cube = Cube(query.select, [], {s.name: m for s, m in matricies})
cube.frum = query
return cube
def format_cube_from_aggop(decoders, aggs, start, query, select):
agg = drill(aggs)
matricies = [(s, Matrix(dims=[], zeros=(s.aggregate == "count"))) for s in select]
for s, m in matricies:
m[tuple()] = agg[s.pull]
cube = Cube(query.select, [], {s.name: m for s, m in matricies})
cube.frum = query
return cube
def es_fieldop(es, query):
FromES = es09.util.build_es_query(query)
select = listwrap(query.select)
FromES.query = {
"filtered": {
"query": {
"match_all": {}
},
"filter": simplify_esfilter(jx_expression(query.where).to_esfilter())
}
}
FromES.size = coalesce(query.limit, 200000)
FromES.fields = FlatList()
for s in select.value:
if s == "*":
FromES.fields = None
elif isinstance(s, list):
FromES.fields.extend(s)
elif isinstance(s, Mapping):
FromES.fields.extend(s.values())
else:
FromES.fields.append(s)
FromES.sort = [{s.field: "asc" if s.sort >= 0 else "desc"} for s in query.sort]
data = es09.util.post(es, FromES, query.limit)
T = data.hits.hits
matricies = {}
for s in select:
if s.value == "*":
matricies[s.name] = Matrix.wrap([t._source for t in T])
elif isinstance(s.value, Mapping):
# for k, v in s.value.items():
# matricies[join_field(split_field(s.name)+[k])] = Matrix.wrap([unwrap(t.fields)[v] for t in T])
matricies[s.name] = Matrix.wrap([{k: unwrap(t.fields).get(v, None) for k, v in s.value.items()}for t in T])
elif isinstance(s.value, list):
matricies[s.name] = Matrix.wrap([tuple(unwrap(t.fields).get(ss, None) for ss in s.value) for t in T])
elif not s.value:
matricies[s.name] = Matrix.wrap([unwrap(t.fields).get(s.value, None) for t in T])
else:
try:
matricies[s.name] = Matrix.wrap([unwrap(t.fields).get(s.value, None) for t in T])
except Exception as e:
Log.error("", e)
cube = Cube(query.select, query.edges, matricies, frum=query)
cube.frum = query
return cube
def es_deepop(es, mvel, query):
FromES = es09.util.build_es_query(query)
select = query.edges
temp_query = query.copy()
temp_query.select = select
temp_query.edges = DictList()
FromES.facets.mvel = {
"terms": {
"script_field": mvel.code(temp_query),
"size": query.limit
},
"facet_filter":
simplify_esfilter(jx_expression(query.where).to_esfilter())
}
data = es09.util.post(es, FromES, query.limit)
rows = unpack_terms(data.facets.mvel, query.edges)
terms = zip(*rows)
# NUMBER ALL EDGES FOR JSON EXPRESSION INDEXING
edges = query.edges
for f, e in enumerate(edges):
for r in terms[f]:
e.domain.getPartByKey(r)
e.index = f
for p, part in enumerate(e.domain.partitions):
part.dataIndex = p
e.domain.NULL.dataIndex = len(e.domain.partitions)
# MAKE CUBE
dims = [len(e.domain.partitions) for e in query.edges]
output = Matrix(*dims)
# FILL CUBE
for r in rows:
term_coord = [
e.domain.getPartByKey(r[i]).dataIndex for i, e in enumerate(edges)
]
output[term_coord] = SUM(output[term_coord], r[-1])
cube = Cube(query.select, query.edges, {query.select.name: output})
cube.frum = query
return cube
def es_deepop(es, mvel, query):
FromES = es09.util.build_es_query(query)
select = query.edges
temp_query = query.copy()
temp_query.select = select
temp_query.edges = FlatList()
FromES.facets.mvel = {
"terms": {
"script_field": mvel.code(temp_query),
"size": query.limit
},
"facet_filter": simplify_esfilter(jx_expression(query.where).to_esfilter())
}
data = es09.util.post(es, FromES, query.limit)
rows = unpack_terms(data.facets.mvel, query.edges)
terms = zip(*rows)
# NUMBER ALL EDGES FOR JSON EXPRESSION INDEXING
edges = query.edges
for f, e in enumerate(edges):
for r in terms[f]:
e.domain.getPartByKey(r)
e.index = f
for p, part in enumerate(e.domain.partitions):
part.dataIndex = p
e.domain.NULL.dataIndex = len(e.domain.partitions)
# MAKE CUBE
dims = [len(e.domain.partitions) for e in query.edges]
output = Matrix(*dims)
# FILL CUBE
for r in rows:
term_coord = [e.domain.getPartByKey(r[i]).dataIndex for i, e in enumerate(edges)]
output[term_coord] = SUM(output[term_coord], r[-1])
cube = Cube(query.select, query.edges, {query.select.name: output})
cube.frum = query
return cube
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
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
def es_terms_stats(esq, mvel, query):
select = listwrap(query.select)
facetEdges = [] # EDGES THAT WILL REQUIRE A FACET FOR EACH PART
termsEdges = FlatList()
specialEdge = None
special_index = -1
# A SPECIAL EDGE IS ONE THAT HAS AN UNDEFINED NUMBER OF PARTITIONS AT QUERY TIME
# FIND THE specialEdge, IF ONE
for f, tedge in enumerate(query.edges):
if tedge.domain.type in domains.KNOWN:
for p, part in enumerate(tedge.domain.partitions):
part.dataIndex = p
# FACETS ARE ONLY REQUIRED IF SQL JOIN ON DOMAIN IS REQUIRED (RANGE QUERY)
# OR IF WE ARE NOT SIMPLY COUNTING
# OR IF NO SCRIPTING IS ALLOWED (SOME OTHER CODE IS RESPONSIBLE FOR SETTING isFacet)
# OR IF WE JUST WANT TO FORCE IT :)
# OF COURSE THE default EDGE IS NOT EXPLICIT, SO MUST BE A TERM
facetEdges.append(tedge)
else:
if specialEdge:
Log.error("There is more than one open-ended edge: self can not be handled")
specialEdge = tedge
special_index = f
termsEdges.append(tedge)
if not specialEdge:
# WE SERIOUSLY WANT A SPECIAL EDGE, OTHERWISE WE WILL HAVE TOO MANY FACETS
# THE BIGGEST EDGE MAY BE COLLAPSED TO A TERM, MAYBE?
num_parts = 0
special_index = -1
for i, e in enumerate(facetEdges):
l = len(e.domain.partitions)
if ((e.value and is_keyword(e.value)) or len(e.domain.dimension.fields) == 1) and l > num_parts:
num_parts = l
specialEdge = e
special_index = i
facetEdges.pop(special_index)
termsEdges.append(specialEdge)
total_facets = PRODUCT(len(f.domain.partitions) for f in facetEdges)*len(select)
if total_facets > 100:
# WE GOT A PROBLEM, LETS COUNT THE SIZE OF REALITY:
counts = esq.query({
"from": query.frum,
"select": {"aggregate": "count"},
"edges": facetEdges,
"where": query.where,
"limit": query.limit
})
esFacets = []
def add_facet(value, parts, cube):
if value:
esFacets.append(parts)
counts["count"].forall(add_facet)
Log.note("{{theory_count}} theoretical combinations, {{real_count}} actual combos found", real_count= len(esFacets), theory_count=total_facets)
if not esFacets:
# MAKE EMPTY CUBE
matricies = {}
dims = [len(e.domain.partitions) + (1 if e.allowNulls else 0) for e in query.edges]
for s in select:
matricies[s.name] = Matrix(*dims)
cube = Cube(query.select, query.edges, matricies)
cube.frum = query
return cube
else:
# GENERATE ALL COMBOS
esFacets = getAllEdges(facetEdges)
calcTerm = compileEdges2Term(mvel, termsEdges, FlatList())
term2parts = calcTerm.term2parts
if len(esFacets) * len(select) > 1000:
Log.error("not implemented yet") # WE HAVE SOME SERIOUS PERMUTATIONS, WE MUST ISSUE MULTIPLE QUERIES
pass
FromES = build_es_query(query)
for s in select:
for parts in esFacets:
condition = FlatList()
constants = FlatList()
name = [literal_field(s.name)]
for f, fedge in enumerate(facetEdges):
name.append(str(parts[f].dataIndex))
condition.append(buildCondition(mvel, fedge, parts[f]))
constants.append({"name": fedge.domain.name, "value": parts[f]})
condition.append(query.where)
name = ",".join(name)
FromES.facets[name] = {
"terms_stats": {
"key_field": calcTerm.field,
"value_field": s.value if is_keyword(s.value) else None,
"value_script": mvel.compile_expression(s.value) if not is_keyword(s.value) else None,
"size": coalesce(query.limit, 200000)
}
}
if condition:
FromES.facets[name].facet_filter = simplify_esfilter({"and": condition})
data = es09.util.post(esq.es, FromES, query.limit)
if specialEdge.domain.type not in domains.KNOWN:
# WE BUILD THE PARTS BASED ON THE RESULTS WE RECEIVED
partitions = FlatList()
map = {}
for facetName, parts in data.facets.items():
for stats in parts.terms:
if not map[stats]:
part = {"value": stats, "name": stats}
partitions.append(part)
map[stats] = part
partitions.sort(specialEdge.domain.compare)
for p, part in enumerate(partitions):
part.dataIndex = p
specialEdge.domain.map = map
specialEdge.domain.partitions = partitions
# MAKE CUBE
matricies = {}
dims = [len(e.domain.partitions) + (1 if e.allowNulls else 0) for e in query.edges]
for s in select:
matricies[s.name] = Matrix(*dims)
name2agg = {s.name: aggregates[s.aggregate] for s in select}
# FILL CUBE
for edgeName, parts in data.facets.items():
temp = edgeName.split(",")
pre_coord = tuple(int(c) for c in temp[1:])
sname = temp[0]
for stats in parts.terms:
if specialEdge:
special = term2parts(stats.term)[0]
coord = pre_coord[:special_index]+(special.dataIndex, )+pre_coord[special_index:]
else:
coord = pre_coord
matricies[sname][coord] = stats[name2agg[sname]]
cube = Cube(query.select, query.edges, matricies)
cube.frum = query
return cube
matricies[s.name] = Matrix.wrap([
tuple(unwrap(t.fields).get(ss, None) for ss in s.value)
for t in T
])
elif not s.value:
matricies[s.name] = Matrix.wrap(
[unwrap(t.fields).get(s.value, None) for t in T])
else:
try:
matricies[s.name] = Matrix.wrap(
[unwrap(t.fields).get(s.value, None) for t in T])
except Exception, e:
Log.error("", e)
cube = Cube(query.select, query.edges, matricies, frum=query)
cube.frum = query
return cube
def is_setop(query):
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:
elif isinstance(s.value, Mapping):
# for k, v in s.value.items():
# matricies[join_field(split_field(s.name)+[k])] = Matrix.wrap([unwrap(t.fields)[v] for t in T])
matricies[s.name] = Matrix.wrap([{k: unwrap(t.fields).get(v, None) for k, v in s.value.items()}for t in T])
elif isinstance(s.value, list):
matricies[s.name] = Matrix.wrap([tuple(unwrap(t.fields).get(ss, None) for ss in s.value) for t in T])
elif not s.value:
matricies[s.name] = Matrix.wrap([unwrap(t.fields).get(s.value, None) for t in T])
else:
try:
matricies[s.name] = Matrix.wrap([unwrap(t.fields).get(s.value, None) for t in T])
except Exception, e:
Log.error("", e)
cube = Cube(query.select, query.edges, matricies, frum=query)
cube.frum = query
return cube
def is_setop(query):
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 domains.ALGEBRAIC and e.domain.interval == "none") for e in query.edges)
def es_terms_stats(esq, mvel, query):
select = listwrap(query.select)
facetEdges = [] # EDGES THAT WILL REQUIRE A FACET FOR EACH PART
termsEdges = DictList()
specialEdge = None
special_index = -1
# A SPECIAL EDGE IS ONE THAT HAS AN UNDEFINED NUMBER OF PARTITIONS AT QUERY TIME
# FIND THE specialEdge, IF ONE
for f, tedge in enumerate(query.edges):
if tedge.domain.type in domains.KNOWN:
for p, part in enumerate(tedge.domain.partitions):
part.dataIndex = p
# FACETS ARE ONLY REQUIRED IF SQL JOIN ON DOMAIN IS REQUIRED (RANGE QUERY)
# OR IF WE ARE NOT SIMPLY COUNTING
# OR IF NO SCRIPTING IS ALLOWED (SOME OTHER CODE IS RESPONSIBLE FOR SETTING isFacet)
# OR IF WE JUST WANT TO FORCE IT :)
# OF COURSE THE default EDGE IS NOT EXPLICIT, SO MUST BE A TERM
facetEdges.append(tedge)
else:
if specialEdge:
Log.error("There is more than one open-ended edge: self can not be handled")
specialEdge = tedge
special_index = f
termsEdges.append(tedge)
if not specialEdge:
# WE SERIOUSLY WANT A SPECIAL EDGE, OTHERWISE WE WILL HAVE TOO MANY FACETS
# THE BIGGEST EDGE MAY BE COLLAPSED TO A TERM, MAYBE?
num_parts = 0
special_index = -1
for i, e in enumerate(facetEdges):
l = len(e.domain.partitions)
if ((e.value and is_keyword(e.value)) or len(e.domain.dimension.fields) == 1) and l > num_parts:
num_parts = l
specialEdge = e
special_index = i
facetEdges.pop(special_index)
termsEdges.append(specialEdge)
total_facets = PRODUCT(len(f.domain.partitions) for f in facetEdges)*len(select)
if total_facets > 100:
# WE GOT A PROBLEM, LETS COUNT THE SIZE OF REALITY:
counts = esq.query({
"from": query.frum,
"select": {"aggregate": "count"},
"edges": facetEdges,
"where": query.where,
"limit": query.limit
})
esFacets = []
def add_facet(value, parts, cube):
if value:
esFacets.append(parts)
counts["count"].forall(add_facet)
Log.note("{{theory_count}} theoretical combinations, {{real_count}} actual combos found", real_count= len(esFacets), theory_count=total_facets)
if not esFacets:
# MAKE EMPTY CUBE
matricies = {}
dims = [len(e.domain.partitions) + (1 if e.allowNulls else 0) for e in query.edges]
for s in select:
matricies[s.name] = Matrix(*dims)
cube = Cube(query.select, query.edges, matricies)
cube.frum = query
return cube
else:
# GENERATE ALL COMBOS
esFacets = getAllEdges(facetEdges)
calcTerm = compileEdges2Term(mvel, termsEdges, DictList())
term2parts = calcTerm.term2parts
if len(esFacets) * len(select) > 1000:
Log.error("not implemented yet") # WE HAVE SOME SERIOUS PERMUTATIONS, WE MUST ISSUE MULTIPLE QUERIES
pass
FromES = build_es_query(query)
for s in select:
for parts in esFacets:
condition = DictList()
constants = DictList()
name = [literal_field(s.name)]
for f, fedge in enumerate(facetEdges):
name.append(str(parts[f].dataIndex))
condition.append(buildCondition(mvel, fedge, parts[f]))
constants.append({"name": fedge.domain.name, "value": parts[f]})
condition.append(query.where)
name = ",".join(name)
FromES.facets[name] = {
"terms_stats": {
"key_field": calcTerm.field,
"value_field": s.value if is_keyword(s.value) else None,
"value_script": mvel.compile_expression(s.value) if not is_keyword(s.value) else None,
"size": coalesce(query.limit, 200000)
}
}
if condition:
FromES.facets[name].facet_filter = simplify_esfilter({"and": condition})
data = es09.util.post(esq.es, FromES, query.limit)
if specialEdge.domain.type not in domains.KNOWN:
# WE BUILD THE PARTS BASED ON THE RESULTS WE RECEIVED
partitions = DictList()
map = {}
for facetName, parts in data.facets.items():
for stats in parts.terms:
if not map[stats]:
part = {"value": stats, "name": stats}
partitions.append(part)
map[stats] = part
partitions.sort(specialEdge.domain.compare)
for p, part in enumerate(partitions):
part.dataIndex = p
specialEdge.domain.map = map
specialEdge.domain.partitions = partitions
# MAKE CUBE
matricies = {}
dims = [len(e.domain.partitions) + (1 if e.allowNulls else 0) for e in query.edges]
for s in select:
matricies[s.name] = Matrix(*dims)
name2agg = {s.name: aggregates[s.aggregate] for s in select}
# FILL CUBE
for edgeName, parts in data.facets.items():
temp = edgeName.split(",")
pre_coord = tuple(int(c) for c in temp[1:])
sname = temp[0]
for stats in parts.terms:
if specialEdge:
special = term2parts(stats.term)[0]
coord = pre_coord[:special_index]+(special.dataIndex, )+pre_coord[special_index:]
else:
coord = pre_coord
matricies[sname][coord] = stats[name2agg[sname]]
cube = Cube(query.select, query.edges, matricies)
cube.frum = query
return cube
