def to_sql(self, schema, not_null=False, boolean=False):
value = SQLang[self.expr].partial_eval()
missing_value = value.missing().partial_eval()
if not is_op(missing_value, MissingOp):
return missing_value.to_sql(schema)
value_sql = value.to_sql(schema)
if len(value_sql) > 1:
return wrap([{"name": ".", "sql": {"b": SQL_FALSE}}])
acc = []
for c in value_sql:
for t, v in c.sql.items():
if t in "bn":
acc.append(ConcatSQL(sql_iso(v), SQL_IS_NULL))
if t == "s":
acc.append(ConcatSQL(
sql_iso(sql_iso(v), SQL_IS_NULL),
SQL_OR,
sql_iso(sql_iso(v), SQL_EQ, SQL_EMPTY_STRING)
))
if not acc:
return wrap([{"name": ".", "sql": {"b": SQL_TRUE}}])
else:
return wrap([{"name": ".", "sql": {"b": SQL_AND.join(acc)}}])
def to_sql(self, schema, not_null=False, boolean=False):
lhs = SQLang[self.lhs].partial_eval()
rhs = SQLang[self.rhs].partial_eval()
lhs_sql = lhs.to_sql(schema, not_null=True)
rhs_sql = rhs.to_sql(schema, not_null=True)
if is_literal(rhs) and lhs_sql[0].sql.b != None and rhs.value in ("T",
"F"):
rhs_sql = BooleanOp(rhs).to_sql(schema)
if is_literal(lhs) and rhs_sql[0].sql.b != None and lhs.value in ("T",
"F"):
lhs_sql = BooleanOp(lhs).to_sql(schema)
if len(lhs_sql) != len(rhs_sql):
Log.error("lhs and rhs have different dimensionality!?")
acc = []
for l, r in zip(lhs_sql, rhs_sql):
for t in "bsnj":
if r.sql[t] == None:
if l.sql[t] == None:
pass
else:
acc.append(ConcatSQL(l.sql[t], SQL_IS_NULL))
elif l.sql[t] == None:
acc.append(ConcatSQL(r.sql[t], SQL_IS_NULL))
else:
acc.append(
ConcatSQL(sql_iso(l.sql[t]), SQL_EQ,
sql_iso(r.sql[t])))
if not acc:
return FALSE.to_sql(schema)
else:
return wrap([{"name": ".", "sql": {"b": JoinSQL(SQL_OR, acc)}}])
def _nest_column(self, column):
new_path, type_ = untyped_column(column.es_column)
if type_ != SQL_NESTED_TYPE:
Log.error("only nested types can be nested")
destination_table = concat_field(self.fact_name, new_path)
existing_table = concat_field(self.fact_name, column.nested_path[0])
# FIND THE INNER COLUMNS WE WILL BE MOVING
moving_columns = []
for c in self.columns:
if destination_table != column.es_index and column.es_column == c.es_column:
moving_columns.append(c)
c.nested_path = new_path
# TODO: IF THERE ARE CHILD TABLES, WE MUST UPDATE THEIR RELATIONS TOO?
# LOAD THE COLUMNS
data = self.namespace.db.about(destination_table)
if not data:
# DEFINE A NEW TABLE
command = (
SQL_CREATE + quote_column(destination_table) + sql_iso(sql_list([
quoted_UID + "INTEGER",
quoted_PARENT + "INTEGER",
quoted_ORDER + "INTEGER",
"PRIMARY KEY " + sql_iso(quoted_UID),
"FOREIGN KEY " + sql_iso(quoted_PARENT) + " REFERENCES " + quote_column(existing_table) + sql_iso(quoted_UID)
]))
)
with self.namespace.db.transaction() as t:
t.execute(command)
self.add_table([new_path]+column.nested_path)
# TEST IF THERE IS ANY DATA IN THE NEW NESTED ARRAY
if not moving_columns:
return
column.es_index = destination_table
with self.namespace.db.transaction() as t:
t.execute(
"ALTER TABLE " + quote_column(destination_table) +
" ADD COLUMN " + quote_column(column.es_column) + " " + column.es_type
)
# Deleting parent columns
for col in moving_columns:
column = col.es_column
tmp_table = "tmp_" + existing_table
columns = list(map(text, t.query(SQL_SELECT + SQL_STAR + SQL_FROM + quote_column(existing_table) + SQL_LIMIT + SQL_ZERO).header))
t.execute(
"ALTER TABLE " + quote_column(existing_table) +
" RENAME TO " + quote_column(tmp_table)
)
t.execute(
SQL_CREATE + quote_column(existing_table) + SQL_AS +
SQL_SELECT + sql_list([quote_column(c) for c in columns if c != column]) +
SQL_FROM + quote_column(tmp_table)
)
t.execute("DROP TABLE " + quote_column(tmp_table))
def to_sql(self, schema, not_null=False, boolean=False):
default = self.default.to_sql(schema)
if len(self.terms) == 0:
return default
len_sep = LengthOp(self.separator).partial_eval()
no_sep = is_literal(len_sep) and len_sep.value == 0
sep = SQLang[self.separator].to_sql(schema)[0].sql.s
acc = []
for t in self.terms:
t = SQLang[t]
missing = t.missing().partial_eval()
term = t.to_sql(schema, not_null=True)[0].sql
if term.s:
term_sql = term.s
elif term.n:
term_sql = "cast(" + term.n + " as text)"
else:
term_sql = (SQL_CASE + SQL_WHEN + term.b + SQL_THEN +
quote_value("true") + SQL_ELSE +
quote_value("false") + SQL_END)
if no_sep:
sep_term = term_sql
else:
sep_term = sql_iso(sql_concat_text([sep, term_sql]))
if isinstance(missing, TrueOp):
acc.append(SQL_EMPTY_STRING)
elif missing:
acc.append(
SQL_CASE + SQL_WHEN +
sql_iso(missing.to_sql(schema, boolean=True)[0].sql.b) +
SQL_THEN + SQL_EMPTY_STRING + SQL_ELSE + sep_term +
SQL_END)
else:
acc.append(sep_term)
if no_sep:
expr_ = sql_concat_text(acc)
else:
expr_ = sql_call(
"SUBSTR", sql_concat_text(acc),
ConcatSQL(
LengthOp(self.separator).to_sql(schema)[0].sql.n, SQL_PLUS,
SQL_ONE))
return SQLScript(
expr=expr_,
data_type=STRING,
frum=self,
miss=self.missing(),
many=False,
schema=schema,
)
def _inequality_to_sql(self, schema, not_null=False, boolean=False, many=True):
op, identity = _sql_operators[self.op]
lhs = NumberOp(self.lhs).partial_eval().to_sql(schema, not_null=True)[0].sql.n
rhs = NumberOp(self.rhs).partial_eval().to_sql(schema, not_null=True)[0].sql.n
sql = sql_iso(lhs) + op + sql_iso(rhs)
output = SQLScript(
data_type=BOOLEAN,
expr=sql,
frum=self,
miss=OrOp([self.lhs.missing(), self.rhs.missing()]),
schema=schema,
)
return output
def to_sql(self, schema, not_null=False, boolean=False):
acc = []
for term in self.terms:
sqls = SQLang[term].to_sql(schema)
if len(sqls) > 1:
acc.append(SQL_TRUE)
else:
for t, v in sqls[0].sql.items():
if t in ["b", "s", "n"]:
acc.append(
ConcatSQL(
SQL_CASE,
SQL_WHEN,
sql_iso(v),
SQL_IS_NULL,
SQL_THEN,
SQL_ZERO,
SQL_ELSE,
SQL_ONE,
SQL_END,
))
else:
acc.append(SQL_TRUE)
if not acc:
return wrap([{}])
else:
return wrap([{"nanme": ".", "sql": {"n": SQL("+").join(acc)}}])
def to_sql(self, schema, not_null=False, boolean=False):
v = self.value.to_sql(schema)[0].sql
return wrap([{
"name": ".",
"sql": {
"n": "UNIX_TIMESTAMP" + sql_iso(v.n)
}
}])
def _window_op(self, query, window):
# http://www2.sqlite.org/cvstrac/wiki?p=UnsupportedSqlAnalyticalFunctions
if window.value == "rownum":
return (
"ROW_NUMBER()-1 OVER (" +
" PARTITION BY " + sql_iso(sql_list(window.edges.values)) +
SQL_ORDERBY + sql_iso(sql_list(window.edges.sort)) +
") AS " + quote_column(window.name)
)
range_min = text(coalesce(window.range.min, "UNBOUNDED"))
range_max = text(coalesce(window.range.max, "UNBOUNDED"))
return (
sql_aggs[window.aggregate] + sql_iso(window.value.to_sql(schema)) + " OVER (" +
" PARTITION BY " + sql_iso(sql_list(window.edges.values)) +
SQL_ORDERBY + sql_iso(sql_list(window.edges.sort)) +
" ROWS BETWEEN " + range_min + " PRECEDING AND " + range_max + " FOLLOWING " +
") AS " + quote_column(window.name)
)
def to_sql(self, schema, not_null=False, boolean=False):
field = self.field.to_sql(schema)[0].sql
acc = []
for t, v in field.items():
if t in "bns":
acc.append(sql_iso(v + SQL_IS_NOT_NULL))
if not acc:
return wrap([{"name": ".", "sql": {"b": SQL_FALSE}}])
else:
return wrap([{"name": ".", "sql": {"b": SQL_OR.join(acc)}}])
def to_sql(self, schema, not_null=False, boolean=False):
terms = [
SQLang[t].partial_eval().to_sql(schema)[0].sql.n
for t in self.terms
]
return wrap([{
"name": ".",
"sql": {
"n": "min" + sql_iso((sql_list(terms)))
}
}])
def to_sql(self, schema, not_null=False, boolean=False):
lhs = SQLang[self.lhs].to_sql(schema)
rhs = SQLang[self.rhs].to_sql(schema)
acc = []
if len(lhs) != len(rhs):
Log.error("lhs and rhs have different dimensionality!?")
for l, r in zip(lhs, rhs):
for t in "bsnj":
if l.sql[t] == None:
if r.sql[t] == None:
pass
else:
acc.append(sql_iso(r.sql[t]) + SQL_IS_NULL)
elif l.sql[t] is ZERO:
if r.sql[t] == None:
acc.append(SQL_FALSE)
elif r.sql[t] is ZERO:
Log.error(
"Expecting expression to have been simplified already"
)
else:
acc.append(r.sql[t])
else:
if r.sql[t] == None:
acc.append(sql_iso(l.sql[t]) + SQL_IS_NULL)
elif r.sql[t] is ZERO:
acc.append(l.sql[t])
else:
acc.append(
sql_iso(l.sql[t]) + SQL_EQ + sql_iso(r.sql[t]))
if not acc:
return FALSE.to_sql(schema)
else:
return SQLScript(
expr=SQL_OR.join(acc),
frum=self,
data_type=BOOLEAN,
miss=FALSE,
schema=schema,
)
def to_sql(self, schema, not_null=False, boolean=False):
not_expr = NotOp(BooleanOp(self.term)).partial_eval()
if is_op(not_expr, NotOp):
return wrap([{
"name": ".",
"sql": {
"b":
"NOT " + sql_iso(not_expr.term.to_sql(schema)[0].sql.b)
},
}])
else:
return not_expr.to_sql(schema)
def to_sql(self, schema, not_null=False, boolean=False):
if not is_op(self.superset, Literal):
Log.error("Not supported")
j_value = json2value(self.superset.json)
if j_value:
var = SQLang[self.value].to_sql(schema)
sql = SQL_OR.join(
sql_iso(v, SQL_IN, quote_list(j_value))
for t, v in var[0].sql.items())
else:
sql = SQL_FALSE
return wrap([{"name": ".", "sql": {"b": sql}}])
def _binaryop_to_sql(self, schema, not_null=False, boolean=False, many=True):
op, identity = _sql_operators[self.op]
lhs = NumberOp(self.lhs).partial_eval().to_sql(schema, not_null=True)[0].sql.n
rhs = NumberOp(self.rhs).partial_eval().to_sql(schema, not_null=True)[0].sql.n
script = sql_iso(lhs) + op + sql_iso(rhs)
if not_null:
sql = script
else:
missing = OrOp([self.lhs.missing(), self.rhs.missing()]).partial_eval()
if missing is FALSE:
sql = script
else:
sql = (
"CASE WHEN "
+ missing.to_sql(schema, boolean=True)[0].sql.b
+ " THEN NULL ELSE "
+ script
+ " END"
)
return wrap([{"name": ".", "sql": {"n": sql}}])
def to_sql(self, schema, not_null=False, boolean=False):
test = SQLang[self.term].missing().to_sql(schema,
boolean=True)[0].sql.b
value = SQLang[self.term].to_sql(schema, not_null=True)[0].sql
acc = []
for t, v in value.items():
if t == "b":
acc.append(SQL_CASE + SQL_WHEN + sql_iso(test) + SQL_THEN +
SQL_NULL + SQL_WHEN + sql_iso(v) + SQL_THEN +
"'true'" + SQL_ELSE + "'false'" + SQL_END)
elif t == "s":
acc.append(v)
else:
acc.append("RTRIM(RTRIM(CAST" +
sql_iso(v + " as TEXT), " + quote_value("0")) +
", " + quote_value(".") + ")")
if not acc:
return wrap([{}])
elif len(acc) == 1:
return wrap([{"name": ".", "sql": {"s": acc[0]}}])
else:
return wrap([{"name": ".", "sql": {"s": sql_coalesce(acc)}}])
def to_sql(self, schema, not_null=False, boolean=False):
term = SQLang[self.term].partial_eval()
if is_literal(term):
val = term.value
if isinstance(val, text):
sql = quote_value(len(val))
elif isinstance(val, (float, int)):
sql = quote_value(len(value2json(val)))
else:
return Null
else:
value = term.to_sql(schema, not_null=not_null)[0].sql.s
sql = ConcatSQL(SQL("LENGTH"), sql_iso(value))
return wrap([{"name": ".", "sql": {"n": sql}}])
def to_sql(self, schema, not_null=False, boolean=False):
return wrap([{
"name": ".",
"sql": {
"b":
JoinSQL(
SQL_OR,
[
sql_iso(SQLang[t].to_sql(
schema, boolean=True)[0].sql.b) for t in self.terms
],
)
},
}])
def to_sql(self, schema, not_null=False, boolean=False):
lhs = SQLang[self.lhs].to_sql(schema)[0].sql.n
rhs = SQLang[self.rhs].to_sql(schema)[0].sql.n
d = SQLang[self.default].to_sql(schema)[0].sql.n
if lhs and rhs:
if d == None:
return wrap([{
"name": ".",
"sql": {
"n": sql_iso(lhs) + " / " + sql_iso(rhs)
}
}])
else:
return wrap([{
"name": ".",
"sql": {
"n":
sql_coalesce([sql_iso(lhs) + " / " + sql_iso(rhs), d])
},
}])
else:
return Null
def to_sql(self, schema, not_null=False, boolean=False):
lhs = SQLang[self.lhs].to_sql(schema)[0].sql.n
rhs = SQLang[self.rhs].to_sql(schema)[0].sql.n
modifier = lhs + " < 0 "
if text(rhs).strip() != "1":
floor = "CAST" + sql_iso(lhs + "/" + rhs + " AS INTEGER")
sql = sql_iso(sql_iso(floor) + "-" + sql_iso(modifier)) + "*" + rhs
else:
floor = "CAST" + sql_iso(lhs + " AS INTEGER")
sql = sql_iso(floor) + "-" + sql_iso(modifier)
return wrap([{"name": ".", "sql": {"n": sql}}])
def _insert(self, collection):
for nested_path, details in collection.items():
active_columns = wrap(list(details.active_columns))
rows = details.rows
num_rows = len(rows)
table_name = concat_field(self.name, nested_path)
if table_name == self.name:
# DO NOT REQUIRE PARENT OR ORDER COLUMNS
meta_columns = [GUID, UID]
else:
meta_columns = [UID, PARENT, ORDER]
all_columns = meta_columns + active_columns.es_column # ONLY THE PRIMITIVE VALUE COLUMNS
command = ConcatSQL(
SQL_INSERT, quote_column(table_name),
sql_iso(sql_list(map(quote_column, all_columns))), SQL_VALUES,
sql_list(
sql_iso(
sql_list(quote_value(row.get(c)) for c in all_columns))
for row in unwrap(rows)))
with self.db.transaction() as t:
t.execute(command)
def _make_range_domain(self, domain, column_name):
width = (domain.max - domain.min) / domain.interval
digits = mo_math.floor(mo_math.log10(width - 1))
if digits == 0:
value = quote_column("a", "value")
else:
value = SQL_PLUS.join("1" + ("0" * j) + SQL_STAR + text(chr(ord(b'a') + j)) + ".value" for j in range(digits + 1))
if domain.interval == 1:
if domain.min == 0:
domain = (
SQL_SELECT + sql_alias(value, column_name) +
SQL_FROM + sql_alias(quote_column(DIGITS_TABLE), "a")
)
else:
domain = (
SQL_SELECT + sql_alias(sql_iso(value) + SQL_PLUS + quote_value(domain.min), column_name) +
SQL_FROM + sql_alias(quote_column(DIGITS_TABLE), "a")
)
else:
if domain.min == 0:
domain = ConcatSQL(
SQL_SELECT, sql_alias(value + SQL_STAR + quote_value(domain.interval), column_name),
SQL_FROM, sql_alias(quote_column(DIGITS_TABLE), "a")
)
else:
domain = ConcatSQL(
SQL_SELECT, sql_alias(
sql_iso(value, SQL_STAR, quote_value(domain.interval)) + SQL_PLUS + quote_value(domain.min),
column_name),
SQL_FROM, sql_alias(quote_column(DIGITS_TABLE), "a")
)
for j in range(digits):
domain += SQL_INNER_JOIN + sql_alias(quote_column(DIGITS_TABLE), text(chr(ord(b'a') + j + 1))) + SQL_ON + SQL_TRUE
domain += SQL_WHERE + value + " < " + quote_value(width)
return domain
def multiop_to_sql(self, schema, not_null=False, boolean=False, many=False):
sign, zero = _sql_operators[self.op]
if len(self.terms) == 0:
return SQLang[self.default].to_sql(schema)
elif self.default is NULL:
return sign.join(
sql_call("COALESCE", SQLang[t].to_sql(schema), zero)
for t in self.terms
)
else:
return sql_call(
"COALESCE",
sign.join(sql_iso(SQLang[t].to_sql(schema)) for t in self.terms),
SQLang[self.default].to_sql(schema)
)
def to_sql(self, schema, not_null=False, boolean=False):
if not self.terms:
return wrap([{"name": ".", "sql": {"b": SQL_TRUE}}])
elif all(self.terms):
return wrap([{
"name": ".",
"sql": {
"b":
SQL_AND.join([
sql_iso(SQLang[t].to_sql(schema,
boolean=True)[0].sql.b)
for t in self.terms
])
},
}])
else:
return wrap([{"name": ".", "sql": {"b": SQL_FALSE}}])
def sql(self):
self.miss = self.miss.partial_eval()
if self.miss is TRUE:
return wrap({json_type_to_sql_type[self.data_type]: SQL_NULL})
elif self.miss is FALSE:
return wrap({json_type_to_sql_type[self.data_type]: self.expr})
else:
return wrap(
{
json_type_to_sql_type[self.data_type]: ConcatSQL(
SQL_CASE,
SQL_WHEN,
SQL_NOT,
sql_iso(SQLang[self.miss].to_sql(self.schema)[0].sql.b),
SQL_THEN,
self.expr,
SQL_END,
)
}
)
def to_sql(self, schema, not_null=False, boolean=False, many=False):
return sql_iso(SQLang[self.rhs].to_sql(schema)) + SQL_EQ + sql_iso(
+SQLang[self.lhs].to_sql(schema))
def _groupby_op(self, query, schema):
base_table = schema.snowflake.fact_name
path = schema.nested_path
# base_table, path = tail_field(frum)
# schema = self.snowflake.tables[path].schema
index_to_column = {}
nest_to_alias = {
nested_path: "__" + unichr(ord('a') + i) + "__"
for i, nested_path in enumerate(self.schema.snowflake.query_paths)
}
tables = []
for n, a in nest_to_alias.items():
if startswith_field(path, n):
tables.append({"nest": n, "alias": a})
tables = jx.sort(tables, {"value": {"length": "nest"}})
from_sql = join_field(
[base_table] + split_field(tables[0].nest)) + " " + tables[0].alias
previous = tables[0]
for t in tables[1::]:
from_sql += (SQL_LEFT_JOIN +
quote_column(concat_field(base_table, t.nest)) + " " +
t.alias + SQL_ON + quote_column(t.alias, PARENT) +
SQL_EQ + quote_column(previous.alias, UID))
selects = []
groupby = []
for i, e in enumerate(query.groupby):
for edge_sql in SQLang[e.value].to_sql(schema):
column_number = len(selects)
sql_type, sql = edge_sql.sql.items()[0]
if sql is SQL_NULL and not e.value.var in schema.keys():
Log.error("No such column {{var}}", var=e.value.var)
column_alias = _make_column_name(column_number)
groupby.append(sql)
selects.append(sql_alias(sql, column_alias))
if edge_sql.nested_path == ".":
select_name = edge_sql.name
else:
select_name = "."
index_to_column[column_number] = ColumnMapping(
is_edge=True,
push_name=e.name,
push_column_name=e.name.replace("\\.", "."),
push_column=i,
push_child=select_name,
pull=get_column(column_number),
sql=sql,
column_alias=column_alias,
type=sql_type_to_json_type[sql_type])
for i, select in enumerate(listwrap(query.select)):
column_number = len(selects)
sql_type, sql = SQLang[select.value].to_sql(
schema)[0].sql.items()[0]
if sql == 'NULL' and not select.value.var in schema.keys():
Log.error("No such column {{var}}", var=select.value.var)
# AGGREGATE
if select.value == "." and select.aggregate == "count":
sql = sql_count(SQL_ONE)
else:
sql = sql_call(sql_aggs[select.aggregate], sql)
if select.default != None:
sql = sql_coalesce([sql, quote_value(select.default)])
selects.append(sql_alias(sql, select.name))
index_to_column[column_number] = ColumnMapping(
push_name=select.name,
push_column_name=select.name,
push_column=i + len(query.groupby),
push_child=".",
pull=get_column(column_number),
sql=sql,
column_alias=quote_column(select.name),
type=sql_type_to_json_type[sql_type])
for w in query.window:
selects.append(self._window_op(self, query, w))
where = SQLang[query.where].to_sql(schema)[0].sql.b
command = (SQL_SELECT + (sql_list(selects)) + SQL_FROM + from_sql +
SQL_WHERE + where + SQL_GROUPBY + sql_list(groupby))
if query.sort:
command += SQL_ORDERBY + sql_list(
sql_iso(sql[t]) + SQL_IS_NULL + "," + sql[t] +
(" DESC" if s.sort == -1 else "")
for s, sql in [(s, SQLang[s.value].to_sql(schema)[0].sql)
for s in query.sort] for t in "bns" if sql[t])
return command, index_to_column
def basic_multiop_to_sql(self, schema, not_null=False, boolean=False, many=False):
op, identity = _sql_operators[self.op.split("basic.")[1]]
sql = op.join(sql_iso(SQLang[t].to_sql(schema)[0].sql.n) for t in self.terms)
return wrap([{"name": ".", "sql": {"n": sql}}])
def update(self, command):
"""
:param command: EXPECTING dict WITH {"set": s, "clear": c, "where": w} FORMAT
"""
command = wrap(command)
clear_columns = set(listwrap(command['clear']))
# REJECT DEEP UPDATES
touched_columns = command.set.keys() | clear_columns
for c in self.schema.columns:
if c.name in touched_columns and len(c.nested_path) > 1:
Log.error("Deep update not supported")
# ADD NEW COLUMNS
where = jx_expression(command.where) or TRUE
_vars = where.vars()
_map = {
v: c.es_column
for v in _vars for c in self.columns.get(v, Null)
if c.jx_type not in STRUCT
}
where_sql = where.map(_map).to_sql(self.schema)[0].sql.b
new_columns = set(command.set.keys()) - set(
c.name for c in self.schema.columns)
for new_column_name in new_columns:
nested_value = command.set[new_column_name]
ctype = get_jx_type(nested_value)
column = Column(name=new_column_name,
jx_type=ctype,
es_index=self.name,
es_type=json_type_to_sqlite_type(ctype),
es_column=typed_column(new_column_name, ctype),
last_updated=Date.now())
self.add_column(column)
# UPDATE THE NESTED VALUES
for nested_column_name, nested_value in command.set.items():
if get_jx_type(nested_value) == "nested":
nested_table_name = concat_field(self.name, nested_column_name)
nested_table = nested_tables[nested_column_name]
self_primary_key = sql_list(
quote_column(c.es_column) for u in self.uid
for c in self.columns[u])
extra_key_name = UID + text(len(self.uid))
extra_key = [e
for e in nested_table.columns[extra_key_name]][0]
sql_command = (
SQL_DELETE + SQL_FROM + quote_column(nested_table.name) +
SQL_WHERE + "EXISTS" +
sql_iso(SQL_SELECT + SQL_ONE + SQL_FROM +
sql_alias(quote_column(nested_table.name), "n") +
SQL_INNER_JOIN +
sql_iso(SQL_SELECT + self_primary_key + SQL_FROM +
quote_column(abs_schema.fact) + SQL_WHERE +
where_sql) + " t ON " +
SQL_AND.join(
quote_column("t", c.es_column) + SQL_EQ +
quote_column("n", c.es_column)
for u in self.uid for c in self.columns[u])))
self.db.execute(sql_command)
# INSERT NEW RECORDS
if not nested_value:
continue
doc_collection = {}
for d in listwrap(nested_value):
nested_table.flatten(d,
Data(),
doc_collection,
path=nested_column_name)
prefix = SQL_INSERT + quote_column(nested_table.name) + sql_iso(
sql_list([self_primary_key] + [quote_column(extra_key)] + [
quote_column(c.es_column)
for c in doc_collection.get(".", Null).active_columns
]))
# BUILD THE PARENT TABLES
parent = (SQL_SELECT + self_primary_key + SQL_FROM +
quote_column(abs_schema.fact) + SQL_WHERE +
jx_expression(command.where).to_sql(schema))
# BUILD THE RECORDS
children = SQL_UNION_ALL.join(
SQL_SELECT +
sql_alias(quote_value(i), extra_key.es_column) +
SQL_COMMA + sql_list(
sql_alias(quote_value(row[c.name]),
quote_column(c.es_column))
for c in doc_collection.get(".", Null).active_columns)
for i, row in enumerate(
doc_collection.get(".", Null).rows))
sql_command = (prefix + SQL_SELECT + sql_list([
quote_column("p", c.es_column) for u in self.uid
for c in self.columns[u]
] + [quote_column("c", extra_key)] + [
quote_column("c", c.es_column)
for c in doc_collection.get(".", Null).active_columns
]) + SQL_FROM + sql_iso(parent) + " p" + SQL_INNER_JOIN +
sql_iso(children) + " c" + SQL_ON + SQL_TRUE)
self.db.execute(sql_command)
# THE CHILD COLUMNS COULD HAVE EXPANDED
# ADD COLUMNS TO SELF
for n, cs in nested_table.columns.items():
for c in cs:
column = Column(name=c.name,
jx_type=c.jx_type,
es_type=c.es_type,
es_index=c.es_index,
es_column=c.es_column,
nested_path=[nested_column_name] +
c.nested_path,
last_updated=Date.now())
if c.name not in self.columns:
self.columns[column.name] = {column}
elif c.jx_type not in [
c.jx_type for c in self.columns[c.name]
]:
self.columns[column.name].add(column)
command = ConcatSQL(
SQL_UPDATE, quote_column(self.name), SQL_SET,
sql_list([
quote_column(c.es_column) + SQL_EQ +
quote_value(get_if_type(v, c.jx_type))
for c in self.schema.columns
if c.jx_type != NESTED and len(c.nested_path) == 1
for v in [command.set[c.name]] if v != None
] + [
quote_column(c.es_column) + SQL_EQ + SQL_NULL
for c in self.schema.columns
if (c.name in clear_columns and command.set[c.name] != None
and c.jx_type != NESTED and len(c.nested_path) == 1)
]), SQL_WHERE, where_sql)
with self.db.transaction() as t:
t.execute(command)
def _set_op(self, query):
# GET LIST OF SELECTED COLUMNS
vars_ = UNION([
v.var for select in listwrap(query.select)
for v in select.value.vars()
])
schema = self.schema
known_vars = schema.keys()
active_columns = {".": set()}
for v in vars_:
for c in schema.leaves(v):
nest = c.nested_path[0]
active_columns.setdefault(nest, set()).add(c)
# ANY VARS MENTIONED WITH NO COLUMNS?
for v in vars_:
if not any(startswith_field(cname, v) for cname in known_vars):
active_columns["."].add(
Column(name=v,
jx_type=IS_NULL,
es_column=".",
es_index=".",
es_type='NULL',
nested_path=["."],
last_updated=Date.now()))
# EVERY COLUMN, AND THE INDEX IT TAKES UP
index_to_column = {} # MAP FROM INDEX TO COLUMN (OR SELECT CLAUSE)
index_to_uid = {} # FROM NESTED PATH TO THE INDEX OF UID
sql_selects = [
] # EVERY SELECT CLAUSE (NOT TO BE USED ON ALL TABLES, OF COURSE)
nest_to_alias = {
nested_path[0]: "__" + unichr(ord('a') + i) + "__"
for i, nested_path in enumerate(self.snowflake.query_paths)
}
sorts = []
if query.sort:
for select in query.sort:
col = SQLang[select.value].to_sql(schema)[0]
for t, sql in col.sql.items():
json_type = sql_type_to_json_type[t]
if json_type in STRUCT:
continue
column_number = len(sql_selects)
# SQL HAS ABS TABLE REFERENCE
column_alias = _make_column_name(column_number)
sql_selects.append(sql_alias(sql, column_alias))
if select.sort == -1:
sorts.append(quote_column(column_alias) + SQL_IS_NULL)
sorts.append(quote_column(column_alias) + " DESC")
else:
sorts.append(quote_column(column_alias) + SQL_IS_NULL)
sorts.append(quote_column(column_alias))
primary_doc_details = Data()
# EVERY SELECT STATEMENT THAT WILL BE REQUIRED, NO MATTER THE DEPTH
# WE WILL CREATE THEM ACCORDING TO THE DEPTH REQUIRED
nested_path = []
for step, sub_table in self.snowflake.tables:
nested_path.insert(0, step)
nested_doc_details = {
"sub_table": sub_table,
"children": [],
"index_to_column": {},
"nested_path": nested_path
}
# INSERT INTO TREE
if not primary_doc_details:
primary_doc_details = nested_doc_details
else:
def place(parent_doc_details):
if startswith_field(step,
parent_doc_details['nested_path'][0]):
for c in parent_doc_details['children']:
if place(c):
return True
parent_doc_details['children'].append(
nested_doc_details)
place(primary_doc_details)
alias = nested_doc_details['alias'] = nest_to_alias[step]
# WE ALWAYS ADD THE UID
column_number = index_to_uid[step] = nested_doc_details[
'id_coord'] = len(sql_selects)
sql_select = quote_column(alias, UID)
sql_selects.append(
sql_alias(sql_select, _make_column_name(column_number)))
if step != ".":
# ID AND ORDER FOR CHILD TABLES
index_to_column[column_number] = ColumnMapping(
sql=sql_select,
type="number",
nested_path=nested_path,
column_alias=_make_column_name(column_number))
column_number = len(sql_selects)
sql_select = quote_column(alias, ORDER)
sql_selects.append(
sql_alias(sql_select, _make_column_name(column_number)))
index_to_column[column_number] = ColumnMapping(
sql=sql_select,
type="number",
nested_path=nested_path,
column_alias=_make_column_name(column_number))
# WE DO NOT NEED DATA FROM TABLES WE REQUEST NOTHING FROM
if step not in active_columns:
continue
# ADD SQL SELECT COLUMNS FOR EACH jx SELECT CLAUSE
si = 0
for select in listwrap(query.select):
try:
column_number = len(sql_selects)
select.pull = get_column(column_number)
db_columns = SQLang[select.value].partial_eval().to_sql(
schema)
for column in db_columns:
for t, unsorted_sql in column.sql.items():
json_type = sql_type_to_json_type[t]
if json_type in STRUCT:
continue
column_number = len(sql_selects)
column_alias = _make_column_name(column_number)
sql_selects.append(
sql_alias(unsorted_sql, column_alias))
if startswith_field(schema.path, step) and is_op(
select.value, LeavesOp):
# ONLY FLATTEN primary_nested_path AND PARENTS, NOT CHILDREN
index_to_column[
column_number] = nested_doc_details[
'index_to_column'][
column_number] = ColumnMapping(
push_name=literal_field(
get_property_name(
concat_field(
select.name,
column.name))),
push_child=".",
push_column_name=
get_property_name(
concat_field(
select.name,
column.name)),
push_column=si,
pull=get_column(column_number),
sql=unsorted_sql,
type=json_type,
column_alias=column_alias,
nested_path=nested_path)
si += 1
else:
index_to_column[
column_number] = nested_doc_details[
'index_to_column'][
column_number] = ColumnMapping(
push_name=select.name,
push_child=column.name,
push_column_name=select.name,
push_column=si,
pull=get_column(column_number),
sql=unsorted_sql,
type=json_type,
column_alias=column_alias,
nested_path=nested_path)
finally:
si += 1
where_clause = BooleanOp(query.where).partial_eval().to_sql(
schema, boolean=True)[0].sql.b
unsorted_sql = self._make_sql_for_one_nest_in_set_op(
".", sql_selects, where_clause, active_columns, index_to_column)
for n, _ in self.snowflake.tables:
sorts.append(quote_column(COLUMN + text(index_to_uid[n])))
ordered_sql = ConcatSQL(SQL_SELECT, SQL_STAR, SQL_FROM,
sql_iso(unsorted_sql), SQL_ORDERBY,
sql_list(sorts), SQL_LIMIT,
quote_value(query.limit))
result = self.db.query(ordered_sql)
def _accumulate_nested(rows, row, nested_doc_details, parent_doc_id,
parent_id_coord):
"""
:param rows: REVERSED STACK OF ROWS (WITH push() AND pop())
:param row: CURRENT ROW BEING EXTRACTED
:param nested_doc_details: {
"nested_path": wrap_nested_path(nested_path),
"index_to_column": map from column number to column details
"children": all possible direct decedents' nested_doc_details
}
:param parent_doc_id: the id of the parent doc (for detecting when to step out of loop)
:param parent_id_coord: the column number for the parent id (so we ca extract from each row)
:return: the nested property (usually an array)
"""
previous_doc_id = None
doc = Null
output = []
id_coord = nested_doc_details['id_coord']
while True:
doc_id = row[id_coord]
if doc_id == None or (parent_id_coord is not None and
row[parent_id_coord] != parent_doc_id):
rows.append(
row
) # UNDO PREVIOUS POP (RECORD IS NOT A NESTED RECORD OF parent_doc)
return output
if doc_id != previous_doc_id:
previous_doc_id = doc_id
doc = Null
curr_nested_path = nested_doc_details['nested_path'][0]
index_to_column = nested_doc_details[
'index_to_column'].items()
for i, c in index_to_column:
value = row[i]
if is_list(query.select) or is_op(
query.select.value, LeavesOp):
# ASSIGN INNER PROPERTIES
relative_field = concat_field(
c.push_name, c.push_child)
else: # FACT IS EXPECTED TO BE A SINGLE VALUE, NOT AN OBJECT
relative_field = c.push_child
if relative_field == ".":
if exists(value):
doc = value
elif exists(value):
if doc is Null:
doc = Data()
doc[relative_field] = value
for child_details in nested_doc_details['children']:
# EACH NESTED TABLE MUST BE ASSEMBLED INTO A LIST OF OBJECTS
child_id = row[child_details['id_coord']]
if child_id is not None:
nested_value = _accumulate_nested(
rows, row, child_details, doc_id, id_coord)
if nested_value != None:
push_name = child_details['nested_path'][0]
if is_list(query.select) or is_op(
query.select.value, LeavesOp):
# ASSIGN INNER PROPERTIES
relative_field = relative_field(
push_name, curr_nested_path)
else: # FACT IS EXPECTED TO BE A SINGLE VALUE, NOT AN OBJECT
relative_field = "."
if relative_field == ".":
doc = unwraplist(nested_value)
else:
doc[relative_field] = unwraplist(nested_value)
output.append(doc)
try:
row = rows.pop()
except IndexError:
return output
cols = tuple(
[i for i in index_to_column.values() if i.push_name != None])
rows = list(reversed(unwrap(result.data)))
if rows:
row = rows.pop()
data = _accumulate_nested(rows, row, primary_doc_details, None,
None)
else:
data = result.data
if query.format == "cube":
# for f, full_name in self.snowflake.tables:
# if f != '.' or (test_dots(cols) and is_list(query.select)):
# num_rows = len(result.data)
# num_cols = MAX([c.push_column for c in cols]) + 1 if len(cols) else 0
# map_index_to_name = {c.push_column: c.push_column_name for c in cols}
# temp_data = [[None] * num_rows for _ in range(num_cols)]
# for rownum, d in enumerate(result.data):
# for c in cols:
# if c.push_child == ".":
# temp_data[c.push_column][rownum] = c.pull(d)
# else:
# column = temp_data[c.push_column][rownum]
# if column is None:
# column = temp_data[c.push_column][rownum] = {}
# column[c.push_child] = c.pull(d)
# output = Data(
# meta={"format": "cube"},
# data={n: temp_data[c] for c, n in map_index_to_name.items()},
# edges=[{
# "name": "rownum",
# "domain": {
# "type": "rownum",
# "min": 0,
# "max": num_rows,
# "interval": 1
# }
# }]
# )
# return output
if is_list(query.select) or is_op(query.select.value, LeavesOp):
num_rows = len(data)
temp_data = {
c.push_column_name: [None] * num_rows
for c in cols
}
for rownum, d in enumerate(data):
for c in cols:
temp_data[c.push_column_name][rownum] = d[c.push_name]
return Data(meta={"format": "cube"},
data=temp_data,
edges=[{
"name": "rownum",
"domain": {
"type": "rownum",
"min": 0,
"max": num_rows,
"interval": 1
}
}])
else:
num_rows = len(data)
map_index_to_name = {
c.push_column: c.push_column_name
for c in cols
}
temp_data = [data]
return Data(meta={"format": "cube"},
data={
n: temp_data[c]
for c, n in map_index_to_name.items()
},
edges=[{
"name": "rownum",
"domain": {
"type": "rownum",
"min": 0,
"max": num_rows,
"interval": 1
}
}])
elif query.format == "table":
# for f, _ in self.snowflake.tables:
# if frum.endswith(f):
# num_column = MAX([c.push_column for c in cols]) + 1
# header = [None] * num_column
# for c in cols:
# header[c.push_column] = c.push_column_name
#
# output_data = []
# for d in result.data:
# row = [None] * num_column
# for c in cols:
# set_column(row, c.push_column, c.push_child, c.pull(d))
# output_data.append(row)
#
# return Data(
# meta={"format": "table"},
# header=header,
# data=output_data
# )
if is_list(query.select) or is_op(query.select.value, LeavesOp):
column_names = [None] * (max(c.push_column for c in cols) + 1)
for c in cols:
column_names[c.push_column] = c.push_column_name
temp_data = []
for rownum, d in enumerate(data):
row = [None] * len(column_names)
for c in cols:
row[c.push_column] = d[c.push_name]
temp_data.append(row)
return Data(meta={"format": "table"},
header=column_names,
data=temp_data)
else:
column_names = listwrap(query.select).name
return Data(meta={"format": "table"},
header=column_names,
data=[[d] for d in data])
else:
# for f, _ in self.snowflake.tables:
# if frum.endswith(f) or (test_dots(cols) and is_list(query.select)):
# data = []
# for d in result.data:
# row = Data()
# for c in cols:
# if c.push_child == ".":
# row[c.push_name] = c.pull(d)
# elif c.num_push_columns:
# tuple_value = row[c.push_name]
# if not tuple_value:
# tuple_value = row[c.push_name] = [None] * c.num_push_columns
# tuple_value[c.push_child] = c.pull(d)
# else:
# row[c.push_name][c.push_child] = c.pull(d)
#
# data.append(row)
#
# return Data(
# meta={"format": "list"},
# data=data
# )
if is_list(query.select) or is_op(query.select.value, LeavesOp):
temp_data = []
for rownum, d in enumerate(data):
row = {}
for c in cols:
row[c.push_column_name] = d[c.push_name]
temp_data.append(row)
return Data(meta={"format": "list"}, data=temp_data)
else:
return Data(meta={"format": "list"}, data=data)
def _make_sql_for_one_nest_in_set_op(
self,
primary_nested_path,
selects, # EVERY SELECT CLAUSE (NOT TO BE USED ON ALL TABLES, OF COURSE
where_clause,
active_columns,
index_to_sql_select # MAP FROM INDEX TO COLUMN (OR SELECT CLAUSE)
):
"""
FOR EACH NESTED LEVEL, WE MAKE A QUERY THAT PULLS THE VALUES/COLUMNS REQUIRED
WE `UNION ALL` THEM WHEN DONE
:param primary_nested_path:
:param selects:
:param where_clause:
:param active_columns:
:param index_to_sql_select:
:return: SQL FOR ONE NESTED LEVEL
"""
parent_alias = "a"
from_clause = []
select_clause = []
children_sql = []
done = []
if not where_clause:
where_clause = SQL_TRUE
# STATEMENT FOR EACH NESTED PATH
for i, (nested_path, sub_table) in enumerate(self.snowflake.tables):
if any(startswith_field(nested_path, d) for d in done):
continue
alias = "__" + unichr(ord('a') + i) + "__"
if primary_nested_path == nested_path:
select_clause = []
# ADD SELECT CLAUSE HERE
for select_index, s in enumerate(selects):
sql_select = index_to_sql_select.get(select_index)
if not sql_select:
select_clause.append(selects[select_index])
continue
if startswith_field(sql_select.nested_path[0],
nested_path):
select_clause.append(
sql_alias(sql_select.sql, sql_select.column_alias))
else:
# DO NOT INCLUDE DEEP STUFF AT THIS LEVEL
select_clause.append(
sql_alias(SQL_NULL, sql_select.column_alias))
if nested_path == ".":
from_clause.append(SQL_FROM)
from_clause.append(
sql_alias(quote_column(self.snowflake.fact_name),
alias))
else:
from_clause.append(SQL_LEFT_JOIN)
from_clause.append(
sql_alias(
quote_column(self.snowflake.fact_name,
sub_table.name), alias))
from_clause.append(SQL_ON)
from_clause.append(quote_column(alias, PARENT))
from_clause.append(SQL_EQ)
from_clause.append(quote_column(parent_alias, UID))
where_clause = sql_iso(
where_clause) + SQL_AND + quote_column(alias,
ORDER) + " > 0"
parent_alias = alias
elif startswith_field(primary_nested_path, nested_path):
# PARENT TABLE
# NO NEED TO INCLUDE COLUMNS, BUT WILL INCLUDE ID AND ORDER
if nested_path == ".":
from_clause.append(SQL_FROM)
from_clause.append(
sql_alias(quote_column(self.snowflake.fact_name),
alias))
else:
parent_alias = alias = unichr(ord('a') + i - 1)
from_clause.append(SQL_LEFT_JOIN)
from_clause.append(
sql_alias(
quote_column(self.snowflake.fact_name,
sub_table.name), alias))
from_clause.append(SQL_ON)
from_clause.append(quote_column(alias, PARENT))
from_clause.append(SQL_EQ)
from_clause.append(quote_column(parent_alias, UID))
where_clause = sql_iso(
where_clause) + SQL_AND + quote_column(
parent_alias, ORDER) + " > 0"
parent_alias = alias
elif startswith_field(nested_path, primary_nested_path):
# CHILD TABLE
# GET FIRST ROW FOR EACH NESTED TABLE
from_clause.append(SQL_LEFT_JOIN)
from_clause.append(
sql_alias(
quote_column(self.snowflake.fact_name, sub_table.name),
alias))
from_clause.append(SQL_ON)
from_clause.append(quote_column(alias, PARENT))
from_clause.append(SQL_EQ)
from_clause.append(quote_column(parent_alias, UID))
from_clause.append(SQL_AND)
from_clause.append(quote_column(alias, ORDER))
from_clause.append(SQL_EQ)
from_clause.append(SQL_ZERO)
# IMMEDIATE CHILDREN ONLY
done.append(nested_path)
# NESTED TABLES WILL USE RECURSION
children_sql.append(
self._make_sql_for_one_nest_in_set_op(
nested_path,
selects, # EVERY SELECT CLAUSE (NOT TO BE USED ON ALL TABLES, OF COURSE
where_clause,
active_columns,
index_to_sql_select # MAP FROM INDEX TO COLUMN (OR SELECT CLAUSE)
))
else:
# SIBLING PATHS ARE IGNORED
continue
sql = SQL_UNION_ALL.join([
ConcatSQL(SQL_SELECT, sql_list(select_clause),
ConcatSQL(*from_clause), SQL_WHERE, where_clause)
], *children_sql)
return sql
