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
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
