Add support for computing remainder with Decimal128 operands with more precision on Spark 3.4 [databricks] #8414
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… to compute the remainder when overflow can happen with upcasting Signed-off-by: Navin Kumar <[email protected]>
Signed-off-by: Navin Kumar <[email protected]>
…mainder-decimal128-spark340
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Investigating Databricks compile failure. Looks unrelated to this branch. |
…mainder-decimal128-spark340
Looks like a new build failure with Databricks 11.3. Will file an issue. |
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Blocked until #8460 is resolved |
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revans2
approved these changes
Jun 1, 2023
| @pytest.mark.parametrize('rhs', [DecimalGen(27,7), DecimalGen(30,10), DecimalGen(38,1), DecimalGen(36,0), DecimalGen(28,-7)], ids=idfn) | ||
| def test_mod_mixed_decimal128(lhs, rhs): | ||
| assert_gpu_and_cpu_are_equal_collect( | ||
| lambda spark : two_col_df(spark, lhs, rhs).selectExpr("a", "b", f"a % b")) |
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nit: why the format string? f"a % b"???
thirtiseven
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Jun 5, 2023
…e precision on Spark 3.4 [databricks] (NVIDIA#8414) * Add support for longRemainder which uses custom spark-rapids-jni code to compute the remainder when overflow can happen with upcasting Signed-off-by: Navin Kumar <[email protected]> * remove commented out line of code. Signed-off-by: Navin Kumar <[email protected]> --------- Signed-off-by: Navin Kumar <[email protected]>
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Fixes #8330.
Depends on NVIDIA/spark-rapids-jni#1175 being merge first.
This completes #8161 and adds support for computing Remainder w/ Decimal 128 operands where higher precision is required than fits into the DECIMAL128 value. It calls the custom code from the spark-rapids-jni PR when the needed precision for the operands is greater than DECIMAL128_MAX_PRECISION.