1
0
Fork 0
sqlglot/sqlglot/dialects/spark.py

197 lines
7.2 KiB
Python
Raw Normal View History

from __future__ import annotations
import typing as t
from sqlglot import exp
from sqlglot.dialects.dialect import rename_func, unit_to_var
from sqlglot.dialects.hive import _build_with_ignore_nulls
from sqlglot.dialects.spark2 import Spark2, temporary_storage_provider, _build_as_cast
from sqlglot.helper import ensure_list, seq_get
from sqlglot.transforms import (
ctas_with_tmp_tables_to_create_tmp_view,
remove_unique_constraints,
preprocess,
move_partitioned_by_to_schema_columns,
)
def _build_datediff(args: t.List) -> exp.Expression:
"""
Although Spark docs don't mention the "unit" argument, Spark3 added support for
it at some point. Databricks also supports this variant (see below).
For example, in spark-sql (v3.3.1):
- SELECT DATEDIFF('2020-01-01', '2020-01-05') results in -4
- SELECT DATEDIFF(day, '2020-01-01', '2020-01-05') results in 4
See also:
- https://docs.databricks.com/sql/language-manual/functions/datediff3.html
- https://docs.databricks.com/sql/language-manual/functions/datediff.html
"""
unit = None
this = seq_get(args, 0)
expression = seq_get(args, 1)
if len(args) == 3:
unit = exp.var(t.cast(exp.Expression, this).name)
this = args[2]
return exp.DateDiff(
this=exp.TsOrDsToDate(this=this), expression=exp.TsOrDsToDate(this=expression), unit=unit
)
def _build_dateadd(args: t.List) -> exp.Expression:
expression = seq_get(args, 1)
if len(args) == 2:
# DATE_ADD(startDate, numDays INTEGER)
# https://docs.databricks.com/en/sql/language-manual/functions/date_add.html
return exp.TsOrDsAdd(
this=seq_get(args, 0), expression=expression, unit=exp.Literal.string("DAY")
)
# DATE_ADD / DATEADD / TIMESTAMPADD(unit, value integer, expr)
# https://docs.databricks.com/en/sql/language-manual/functions/date_add3.html
return exp.TimestampAdd(this=seq_get(args, 2), expression=expression, unit=seq_get(args, 0))
def _normalize_partition(e: exp.Expression) -> exp.Expression:
"""Normalize the expressions in PARTITION BY (<expression>, <expression>, ...)"""
if isinstance(e, str):
return exp.to_identifier(e)
if isinstance(e, exp.Literal):
return exp.to_identifier(e.name)
return e
def _dateadd_sql(self: Spark.Generator, expression: exp.TsOrDsAdd | exp.TimestampAdd) -> str:
if not expression.unit or (
isinstance(expression, exp.TsOrDsAdd) and expression.text("unit").upper() == "DAY"
):
# Coming from Hive/Spark2 DATE_ADD or roundtripping the 2-arg version of Spark3/DB
return self.func("DATE_ADD", expression.this, expression.expression)
this = self.func(
"DATE_ADD",
unit_to_var(expression),
expression.expression,
expression.this,
)
if isinstance(expression, exp.TsOrDsAdd):
# The 3 arg version of DATE_ADD produces a timestamp in Spark3/DB but possibly not
# in other dialects
return_type = expression.return_type
if not return_type.is_type(exp.DataType.Type.TIMESTAMP, exp.DataType.Type.DATETIME):
this = f"CAST({this} AS {return_type})"
return this
class Spark(Spark2):
SUPPORTS_ORDER_BY_ALL = True
class Tokenizer(Spark2.Tokenizer):
STRING_ESCAPES_ALLOWED_IN_RAW_STRINGS = False
RAW_STRINGS = [
(prefix + q, q)
for q in t.cast(t.List[str], Spark2.Tokenizer.QUOTES)
for prefix in ("r", "R")
]
class Parser(Spark2.Parser):
FUNCTIONS = {
**Spark2.Parser.FUNCTIONS,
"ANY_VALUE": _build_with_ignore_nulls(exp.AnyValue),
"DATE_ADD": _build_dateadd,
"DATEADD": _build_dateadd,
"TIMESTAMPADD": _build_dateadd,
"DATEDIFF": _build_datediff,
"DATE_DIFF": _build_datediff,
"TIMESTAMP_LTZ": _build_as_cast("TIMESTAMP_LTZ"),
"TIMESTAMP_NTZ": _build_as_cast("TIMESTAMP_NTZ"),
"TRY_ELEMENT_AT": lambda args: exp.Bracket(
this=seq_get(args, 0),
expressions=ensure_list(seq_get(args, 1)),
offset=1,
safe=True,
),
}
def _parse_generated_as_identity(
self,
) -> (
exp.GeneratedAsIdentityColumnConstraint
| exp.ComputedColumnConstraint
| exp.GeneratedAsRowColumnConstraint
):
this = super()._parse_generated_as_identity()
if this.expression:
return self.expression(exp.ComputedColumnConstraint, this=this.expression)
return this
class Generator(Spark2.Generator):
SUPPORTS_TO_NUMBER = True
PAD_FILL_PATTERN_IS_REQUIRED = False
SUPPORTS_CONVERT_TIMEZONE = True
TYPE_MAPPING = {
**Spark2.Generator.TYPE_MAPPING,
exp.DataType.Type.MONEY: "DECIMAL(15, 4)",
exp.DataType.Type.SMALLMONEY: "DECIMAL(6, 4)",
exp.DataType.Type.UNIQUEIDENTIFIER: "STRING",
exp.DataType.Type.TIMESTAMPLTZ: "TIMESTAMP_LTZ",
exp.DataType.Type.TIMESTAMPNTZ: "TIMESTAMP_NTZ",
}
TRANSFORMS = {
**Spark2.Generator.TRANSFORMS,
exp.ArrayConstructCompact: lambda self, e: self.func(
"ARRAY_COMPACT", self.func("ARRAY", *e.expressions)
),
exp.Create: preprocess(
[
remove_unique_constraints,
lambda e: ctas_with_tmp_tables_to_create_tmp_view(
e, temporary_storage_provider
),
move_partitioned_by_to_schema_columns,
]
),
exp.PartitionedByProperty: lambda self,
e: f"PARTITIONED BY {self.wrap(self.expressions(sqls=[_normalize_partition(e) for e in e.this.expressions], skip_first=True))}",
exp.StartsWith: rename_func("STARTSWITH"),
exp.TsOrDsAdd: _dateadd_sql,
exp.TimestampAdd: _dateadd_sql,
exp.TryCast: lambda self, e: (
self.trycast_sql(e) if e.args.get("safe") else self.cast_sql(e)
),
}
TRANSFORMS.pop(exp.AnyValue)
TRANSFORMS.pop(exp.DateDiff)
TRANSFORMS.pop(exp.Group)
def bracket_sql(self, expression: exp.Bracket) -> str:
if expression.args.get("safe"):
key = seq_get(self.bracket_offset_expressions(expression, index_offset=1), 0)
return self.func("TRY_ELEMENT_AT", expression.this, key)
return super().bracket_sql(expression)
def computedcolumnconstraint_sql(self, expression: exp.ComputedColumnConstraint) -> str:
return f"GENERATED ALWAYS AS ({self.sql(expression, 'this')})"
def anyvalue_sql(self, expression: exp.AnyValue) -> str:
return self.function_fallback_sql(expression)
def datediff_sql(self, expression: exp.DateDiff) -> str:
end = self.sql(expression, "this")
start = self.sql(expression, "expression")
if expression.unit:
return self.func("DATEDIFF", unit_to_var(expression), start, end)
return self.func("DATEDIFF", end, start)