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SNOW-1690923 Encode Intervals #2454

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SNOW-1690923 Encode Intervals #2454

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a05a978
Encoding intervals
sfc-gh-vbudati Oct 15, 2024
5f492e0
Merge branch 'ls-SNOW-1491199-merge-phase0-server-side' into vbudati/…
sfc-gh-vbudati Oct 15, 2024
1905e6c
lint
sfc-gh-vbudati Oct 15, 2024
967121b
update pb2 files, fix _plan.py so that interval test works when ast i…
sfc-gh-vbudati Oct 15, 2024
737eb3a
update tests
sfc-gh-vbudati Oct 15, 2024
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12 changes: 12 additions & 0 deletions src/snowflake/snowpark/_internal/analyzer/expression.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,6 +6,7 @@
import uuid
from typing import TYPE_CHECKING, AbstractSet, Any, Dict, List, Optional, Tuple

import snowflake.snowpark._internal.proto.ast_pb2 as proto
import snowflake.snowpark._internal.utils
from snowflake.snowpark._internal.analyzer.query_plan_analysis_utils import (
PlanNodeCategory,
Expand Down Expand Up @@ -379,7 +380,10 @@ def __init__(
millisecond: Optional[int] = None,
microsecond: Optional[int] = None,
nanosecond: Optional[int] = None,
_emit_ast: bool = True,
) -> None:
from snowflake.snowpark._internal.ast_utils import with_src_position
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Had to import here to prevent circular imports issue.

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So far in the code, we tried to avoid building expressions directly. The reasoning was that Expressions should disappear as they're not a first-class entity in snowpark. Instead we chose an approach where always the caller (i.e. the function that creates Interval) creates the AST and assigns it to the expression if need be. I.e.,

def build_expr_from_snowpark_column_or_python_val(
    expr_builder: proto.Expr, value: ColumnOrLiteral
) -> None:
    """Copy from a Column object's AST, or copy a literal value into an AST expression.

    Args:
        ast (proto.Expr): A previously created Expr() IR entity intance to be filled
        value (ColumnOrLiteral): The value from which to populate the provided ast parameter.

    Raises:
        TypeError: The Expr provided should only be populated from a Snowpark Column with a valid _ast field or a literal value
    """
    if isinstance(value, snowflake.snowpark.Column):
        build_expr_from_snowpark_column(expr_builder, value)
    elif isinstance(value, VALID_PYTHON_TYPES_FOR_LITERAL_VALUE):
        build_expr_from_python_val(expr_builder, value)
    elif isinstance(value, Expression):
        # Expressions must be handled by caller.
        pass
    else:
        raise TypeError(f"{type(value)} is not a valid type for Column or literal AST.")

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we prob. can move the AST logic to build_expr_from_snowpark_column_or_python_val and have an Interval case there. I don't think the original intention of snowpark was to use Interval directly, but rather the make_interval function.


super().__init__()
self.values_dict = {}
if year is not None:
Expand All @@ -405,6 +409,14 @@ def __init__(
if nanosecond is not None:
self.values_dict["NANOSECOND"] = nanosecond

if self._ast is None and _emit_ast:
expr = proto.Expr()
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/home/runner/work/snowpark-python/snowpark-python/src/snowflake/snowpark/_internal/analyzer/expression.py:413:26 - error: "Expr" is not a known member of module "snowflake.snowpark._internal.proto.ast_pb2" (reportGeneralTypeIssues)

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Can you repro locally?

python -m tox -e pyright

It is saying you may need a new version:
"Please install the new version or set PYRIGHT_PYTHON_FORCE_VERSION to latest"

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I get the same errors locally, I'm not sure what to do about the first error though. There's other parts of the code that use proto.Expr() as well so I'm not sure why it's erroring here

ast = with_src_position(expr.sp_interval)
# Set the AST values based on the values_dict.
for k, v in self.values_dict.items():
getattr(ast, k.lower()).value = v
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let's try to avoid indirection via getattr and use the values explicitly. It's much easier to read and reason about :)

self._ast = expr

@property
def sql(self) -> str:
return f"""INTERVAL '{",".join(f"{v} {k}" for k, v in self.values_dict.items())}'"""
Expand Down
876 changes: 439 additions & 437 deletions src/snowflake/snowpark/_internal/proto/ast_pb2.py
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4 changes: 4 additions & 0 deletions src/snowflake/snowpark/mock/_analyzer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -57,6 +57,7 @@
Expression,
FunctionExpression,
InExpression,
Interval,
Like,
ListAgg,
Literal,
Expand Down Expand Up @@ -464,6 +465,9 @@ def analyze(
expr.ignore_nulls,
)

if isinstance(expr, Interval):
return str(expr)

raise SnowparkClientExceptionMessages.PLAN_INVALID_TYPE(
str(expr)
) # pragma: no cover
Expand Down
81 changes: 81 additions & 0 deletions tests/ast/data/interval.test
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Original file line number Diff line number Diff line change
@@ -0,0 +1,81 @@
## TEST CASE

from snowflake.snowpark._internal.analyzer.expression import Interval

df1 = session.create_dataframe(
[
[datetime.datetime(2010, 1, 1), datetime.datetime(2011, 1, 1)],
[datetime.datetime(2012, 1, 1), datetime.datetime(2013, 1, 1)],
],
schema=["a", "b"],
)

df2 = df1.select(
df1["a"]
+ Column(
Interval(
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let's use make_interval here to test. Not sure we should support the Column(Interval(...)) syntax at all.

quarter=1,
month=1,
week=2,
day=2,
hour=2,
minute=3,
second=3,
millisecond=3,
microsecond=4,
nanosecond=4,
)
)
)

df4 = df1.select(df1["a"] + Column(Interval(1234)))

df5 = df1.select(
df1["a"]
+ Column(
Interval(
quarter=1,
month=2,
week=3,
day=4,
hour=5,
minute=6,
second=7
)
)
)

df6 = df1.select(
df1["a"]
+ Column(
Interval(
year=1,
month=2,
week=3,
day=4,
hour=5,
minute=6,
second=7,
millisecond=8,
microsecond=9,
nanosecond=10
)
)
)


## EXPECTED UNPARSER OUTPUT

df1 = session.create_dataframe([[datetime.datetime(2010, 1, 1, 0, 0, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=-18000), name="EST")), datetime.datetime(2011, 1, 1, 0, 0, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=-18000), name="EST"))], [datetime.datetime(2012, 1, 1, 0, 0, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=-18000), name="EST")), datetime.datetime(2013, 1, 1, 0, 0, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=-18000), name="EST"))]], schema=["a", "b"])

df2 = df1.select(df1["a"] + Interval(quarter=1, month=1, week=2, day=2, hour=2, minute=3, second=3, millisecond=3, microsecond=4, nanosecond=4))
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does this work in snowpark?

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@sfc-gh-vbudati sfc-gh-vbudati Oct 15, 2024 •
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I believe it does - I pulled this from test_interval:

def test_interval(session):
    df1 = session.create_dataframe(
        [
            [datetime.datetime(2010, 1, 1), datetime.datetime(2011, 1, 1)],
            [datetime.datetime(2012, 1, 1), datetime.datetime(2013, 1, 1)],
        ],
        schema=["a", "b"],
    )
    df2 = df1.select(
        df1["a"]
        + Column(
            Interval(
                quarters=1,
                months=1,
                weeks=2,
                days=2,
                hours=2,
                minutes=3,
                seconds=3,
                milliseconds=3,
                microseconds=4,
                nanoseconds=4,
            )
        )
    )
    verify_column_result(
        session,
        df2,
        [
            '"(""A"" + INTERVAL \'1 QUARTER,1 MONTH,2 WEEK,2 DAY,2 HOUR,3 MINUTE,3 SECOND,3 MILLISECOND,4 MICROSECOND,4 NANOSECOND\')"',
        ],
        [TimestampType(timezone=TimestampTimeZone.NTZ)],
        None,
    )

but I see that you added the make_interval changes - I'll update my tests accordingly


df4 = df1.select(df1["a"] + Interval(year=1234))

df5 = df1.select(df1["a"] + Interval(quarter=1, month=2, week=3, day=4, hour=5, minute=6, second=7))

df6 = df1.select(df1["a"] + Interval(year=1, month=2, week=3, day=4, hour=5, minute=6, second=7, millisecond=8, microsecond=9, nanosecond=10))

## EXPECTED ENCODED AST

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
4 changes: 0 additions & 4 deletions tests/integ/test_column_names.py
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Expand Up @@ -373,10 +373,6 @@ def test_literal(session, local_testing_mode):
)


@pytest.mark.skipif(
"config.getoption('local_testing_mode', default=False)",
reason="SNOW-1358946: Interval is not supported in Local Testing",
)
def test_interval(session):
df1 = session.create_dataframe(
[
Expand Down
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