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Support yyyyMMdd in GetTimestamp operator for LEGACY mode [databricks] #11449

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Sep 23, 2024
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Support yyyyMMdd in GetTimestamp operator for LEGACY mode [databricks] #11449

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adbbefd
Support yyyyMMdd in GetTimestamp operator for LEGACY mode
Sep 9, 2024
adc9b79
Update cases
Sep 19, 2024
de76521
Refactor a test case
Sep 20, 2024
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3 changes: 3 additions & 0 deletions docs/compatibility.md
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Original file line number Diff line number Diff line change
Expand Up @@ -651,6 +651,7 @@ guaranteed to produce the same results as the CPU:
- `dd/MM/yyyy`
- `yyyy/MM/dd`
- `yyyy-MM-dd`
- `yyyyMMdd`
- `yyyy/MM/dd HH:mm:ss`
- `yyyy-MM-dd HH:mm:ss`

Expand All @@ -659,6 +660,8 @@ LEGACY timeParserPolicy support has the following limitations when running on th
- Only 4 digit years are supported
- The proleptic Gregorian calendar is used instead of the hybrid Julian+Gregorian calendar
that Spark uses in legacy mode
- When format is `yyyyMMdd`, GPU only supports 8 digit strings. Spark supports like 7 digit
`2024101` string while GPU does not support.

## Formatting dates and timestamps as strings

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12 changes: 11 additions & 1 deletion integration_tests/src/main/python/date_time_test.py
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Expand Up @@ -13,7 +13,7 @@
# limitations under the License.

import pytest
from asserts import assert_gpu_and_cpu_are_equal_collect, assert_gpu_fallback_collect, assert_gpu_and_cpu_error
from asserts import assert_gpu_and_cpu_are_equal_collect, assert_gpu_fallback_collect, assert_gpu_and_cpu_error, assert_gpu_and_cpu_are_equal_sql
from conftest import is_utc, is_supported_time_zone, get_test_tz
from data_gen import *
from datetime import date, datetime, timezone
Expand Down Expand Up @@ -459,6 +459,16 @@ def test_to_timestamp(parser_policy):
.select(f.col("a"), f.to_timestamp(f.col("a"), "yyyy-MM-dd HH:mm:ss")),
{ "spark.sql.legacy.timeParserPolicy": parser_policy})

@pytest.mark.skipif(not is_supported_time_zone(), reason="not all time zones are supported now, refer to https://github.com/NVIDIA/spark-rapids/issues/6839, please update after all time zones are supported")
def test_to_timestamp_legacy_mode_yyyyMMdd_format():
gen = StringGen("[0-9]{3}[1-9](0[1-9]|1[0-2])(0[1-9]|[1-2][0-9])")
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assert_gpu_and_cpu_are_equal_sql(
lambda spark : unary_op_df(spark, gen),
"tab",
"select unix_timestamp(a, 'yyyyMMdd'), from_unixtime(unix_timestamp(a, 'yyyyMMdd'), 'yyyyMMdd'), date_format(to_timestamp(a, 'yyyyMMdd'), 'yyyyMMdd') from tab",
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Consider using multi-line strings

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Done

{
'spark.sql.legacy.timeParserPolicy': 'LEGACY',
'spark.rapids.sql.incompatibleDateFormats.enabled': True})

@tz_sensitive_test
@pytest.mark.skipif(not is_supported_time_zone(), reason="not all time zones are supported now, refer to https://github.com/NVIDIA/spark-rapids/issues/6839, please update after all time zones are supported")
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19 changes: 17 additions & 2 deletions sql-plugin/src/main/scala/org/apache/spark/sql/rapids/datetimeExpressions.scala
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Expand Up @@ -640,7 +640,9 @@ object GpuToTimestamp {
"yyyy-MM-dd HH:mm:ss" -> ParseFormatMeta(Option('-'), isTimestamp = true,
raw"\A\d{4}-\d{1,2}-\d{1,2}[ T]\d{1,2}:\d{1,2}:\d{1,2}(\D|\s|\Z)"),
"yyyy/MM/dd HH:mm:ss" -> ParseFormatMeta(Option('/'), isTimestamp = true,
raw"\A\d{4}/\d{1,2}/\d{1,2}[ T]\d{1,2}:\d{1,2}:\d{1,2}(\D|\s|\Z)")
raw"\A\d{4}/\d{1,2}/\d{1,2}[ T]\d{1,2}:\d{1,2}:\d{1,2}(\D|\s|\Z)"),
"yyyyMMdd" -> ParseFormatMeta(None, isTimestamp = false,
raw"\A\d{8}(\D|\s|\Z)")
)

/** remove whitespace before month and day */
Expand Down Expand Up @@ -762,8 +764,21 @@ object GpuToTimestamp {
case RegexReplace(pattern, backref) =>
RegexReplace(pattern.replace('-', '/'), backref.replace('-', '/'))
}
case Some('-') | Some(_) | None =>
case Some('-') | Some(_) =>
regexReplaceRules
case None =>
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// For formats like `yyyyMMdd` that do not contains separator,
// do not need to do regexp replacement rules
// Note: here introduced the following inconsistent behavior compared to Spark
// Spark's behavior:
// to_date('20240101', 'yyyyMMdd') = 2024-01-01
// to_date('202401 01', 'yyyyMMdd') = 2024-01-01
// to_date('2024 0101', 'yyyyMMdd') = null
// GPU behavior:
// to_date('20240101', 'yyyyMMdd') = 2024-01-01
// to_date('202401 01', 'yyyyMMdd') = null
// to_date('2024 0101', 'yyyyMMdd') = null
Seq()
}

// apply each rule in turn to the data
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