def to_esfilter(self, schema):
if is_op(self.value, Variable_):
var = self.value.var
cols = schema.leaves(var)
if not cols:
Log.error("expecting {{var}} to be a column", var=var)
col = first(cols)
var = col.es_column
if col.jx_type == BOOLEAN:
if is_literal(self.superset) and not is_sequence(
self.superset.value):
return {"term": {var: value2boolean(self.superset.value)}}
else:
return {
"terms": {
var: map(value2boolean, self.superset.value)
}
}
else:
if is_literal(self.superset) and not is_sequence(
self.superset.value):
return {"term": {var: self.superset.value}}
else:
return {"terms": {var: self.superset.value}}
else:
return Painless[self].to_es_script(schema).to_esfilter(schema)
def to_esfilter(self, schema):
if is_op(self.value, Variable_):
var = self.value.var
cols = schema.leaves(var)
if not cols:
return MATCH_NONE
col = first(cols)
var = col.es_column
if col.jx_type == BOOLEAN:
if is_literal(
self.superset) and not is_many(self.superset.value):
return {"term": {var: value2boolean(self.superset.value)}}
else:
return {
"terms": {
var: map(value2boolean, self.superset.value)
}
}
else:
if is_literal(
self.superset) and not is_many(self.superset.value):
return {"term": {var: self.superset.value}}
else:
return {"terms": {var: self.superset.value}}
else:
return Painless[self].to_es_script(schema).to_esfilter(schema)
def to_es(self, schema):
value = self.value
if is_op(value, Variable):
var = value.var
cols = schema.leaves(var)
if not cols:
return MATCH_NONE
col = first(cols)
var = col.es_column
if is_literal(self.superset):
if col.jx_type == BOOLEAN:
if is_literal(self.superset) and not is_many(
self.superset.value):
return {
"term": {
var: value2boolean(self.superset.value)
}
}
else:
return {
"terms": {
var:
list(map(value2boolean, self.superset.value))
}
}
else:
if is_literal(self.superset) and not is_many(
self.superset.value):
return {"term": {var: self.superset.value}}
else:
return {"terms": {var: self.superset.value}}
elif is_op(self.superset, TupleOp):
return (OrOp([EqOp([value, s]) for s in self.superset.terms
]).partial_eval().to_es(schema))
if (is_op(value, NestedOp) and is_literal(self.superset)
and is_op(value.select, Variable)):
output = (ES52[NestedOp(
path=value.path,
select=NULL,
where=AndOp([value.where,
InOp([value.select, self.superset])]),
)].exists().partial_eval().to_es(schema))
return output
# THE HARD WAY
return Painless[self].to_es_script(schema).to_es(schema)
def to_esfilter(self, schema):
if is_op(self.value, Variable_):
var = self.value.var
cols = schema.leaves(var)
if not cols:
return MATCH_NONE
col = first(cols)
var = col.es_column
if is_literal(self.superset):
if col.jx_type == BOOLEAN:
if is_literal(self.superset) and not is_many(
self.superset.value):
return {
"term": {
var: value2boolean(self.superset.value)
}
}
else:
return {
"terms": {
var:
list(map(value2boolean, self.superset.value))
}
}
else:
if is_literal(self.superset) and not is_many(
self.superset.value):
return {"term": {var: self.superset.value}}
else:
return {"terms": {var: self.superset.value}}
elif is_op(self.superset, TupleOp):
return (OrOp([
EqOp([self.value, s]) for s in self.superset.terms
]).partial_eval().to_esfilter(schema))
# THE HARD WAY
return Painless[self].to_es_script(schema).to_esfilter(schema)