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[SPARK-20685] Fix BatchPythonEvaluation bug in case of single UDF w/ repeated arg. #17927

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@JoshRosen JoshRosen commented May 9, 2017

What changes were proposed in this pull request?

There's a latent corner-case bug in PySpark UDF evaluation where executing a BatchPythonEvaluation with a single multi-argument UDF where at least one argument value is repeated will crash at execution with a confusing error.

This problem was introduced in #12057: the code there has a fast path for handling a "batch UDF evaluation consisting of a single Python UDF", but that branch incorrectly assumes that a single UDF won't have repeated arguments and therefore skips the code for unpacking arguments from the input row (whose schema may not necessarily match the UDF inputs due to de-duplication of repeated arguments which occurred in the JVM before sending UDF inputs to Python).

This fix here is simply to remove this special-casing: it turns out that the code in the "multiple UDFs" branch just so happens to work for the single-UDF case because Python treats (x) as equivalent to x, not as a single-argument tuple.

How was this patch tested?

New regression test in pyspark.python.sql.tests module (tested and confirmed that it fails before my fix).

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SparkQA commented May 9, 2017

Test build #76707 has finished for PR 17927 at commit 17e69b5.

  • This patch passes all tests.
  • This patch merges cleanly.
  • This patch adds no public classes.

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LGTM

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Thanks! Merging to master/2.2/2.1

asfgit pushed a commit that referenced this pull request May 10, 2017
…repeated arg.

## What changes were proposed in this pull request?

There's a latent corner-case bug in PySpark UDF evaluation where executing a `BatchPythonEvaluation` with a single multi-argument UDF where _at least one argument value is repeated_ will crash at execution with a confusing error.

This problem was introduced in #12057: the code there has a fast path for handling a "batch UDF evaluation consisting of a single Python UDF", but that branch incorrectly assumes that a single UDF won't have repeated arguments and therefore skips the code for unpacking arguments from the input row (whose schema may not necessarily match the UDF inputs due to de-duplication of repeated arguments which occurred in the JVM before sending UDF inputs to Python).

This fix here is simply to remove this special-casing: it turns out that the code in the "multiple UDFs" branch just so happens to work for the single-UDF case because Python treats `(x)` as equivalent to `x`, not as a single-argument tuple.

## How was this patch tested?

New regression test in `pyspark.python.sql.tests` module (tested and confirmed that it fails before my fix).

Author: Josh Rosen <joshrosen@databricks.com>

Closes #17927 from JoshRosen/SPARK-20685.

(cherry picked from commit 8ddbc43)
Signed-off-by: Xiao Li <gatorsmile@gmail.com>
@asfgit asfgit closed this in 8ddbc43 May 10, 2017
asfgit pushed a commit that referenced this pull request May 10, 2017
…repeated arg.

## What changes were proposed in this pull request?

There's a latent corner-case bug in PySpark UDF evaluation where executing a `BatchPythonEvaluation` with a single multi-argument UDF where _at least one argument value is repeated_ will crash at execution with a confusing error.

This problem was introduced in #12057: the code there has a fast path for handling a "batch UDF evaluation consisting of a single Python UDF", but that branch incorrectly assumes that a single UDF won't have repeated arguments and therefore skips the code for unpacking arguments from the input row (whose schema may not necessarily match the UDF inputs due to de-duplication of repeated arguments which occurred in the JVM before sending UDF inputs to Python).

This fix here is simply to remove this special-casing: it turns out that the code in the "multiple UDFs" branch just so happens to work for the single-UDF case because Python treats `(x)` as equivalent to `x`, not as a single-argument tuple.

## How was this patch tested?

New regression test in `pyspark.python.sql.tests` module (tested and confirmed that it fails before my fix).

Author: Josh Rosen <joshrosen@databricks.com>

Closes #17927 from JoshRosen/SPARK-20685.

(cherry picked from commit 8ddbc43)
Signed-off-by: Xiao Li <gatorsmile@gmail.com>
@JoshRosen JoshRosen deleted the SPARK-20685 branch May 10, 2017 23:55
liyichao pushed a commit to liyichao/spark that referenced this pull request May 24, 2017
…repeated arg.

## What changes were proposed in this pull request?

There's a latent corner-case bug in PySpark UDF evaluation where executing a `BatchPythonEvaluation` with a single multi-argument UDF where _at least one argument value is repeated_ will crash at execution with a confusing error.

This problem was introduced in apache#12057: the code there has a fast path for handling a "batch UDF evaluation consisting of a single Python UDF", but that branch incorrectly assumes that a single UDF won't have repeated arguments and therefore skips the code for unpacking arguments from the input row (whose schema may not necessarily match the UDF inputs due to de-duplication of repeated arguments which occurred in the JVM before sending UDF inputs to Python).

This fix here is simply to remove this special-casing: it turns out that the code in the "multiple UDFs" branch just so happens to work for the single-UDF case because Python treats `(x)` as equivalent to `x`, not as a single-argument tuple.

## How was this patch tested?

New regression test in `pyspark.python.sql.tests` module (tested and confirmed that it fails before my fix).

Author: Josh Rosen <joshrosen@databricks.com>

Closes apache#17927 from JoshRosen/SPARK-20685.
jzhuge pushed a commit to jzhuge/spark that referenced this pull request Aug 20, 2018
…repeated arg.

There's a latent corner-case bug in PySpark UDF evaluation where executing a `BatchPythonEvaluation` with a single multi-argument UDF where _at least one argument value is repeated_ will crash at execution with a confusing error.

This problem was introduced in apache#12057: the code there has a fast path for handling a "batch UDF evaluation consisting of a single Python UDF", but that branch incorrectly assumes that a single UDF won't have repeated arguments and therefore skips the code for unpacking arguments from the input row (whose schema may not necessarily match the UDF inputs due to de-duplication of repeated arguments which occurred in the JVM before sending UDF inputs to Python).

This fix here is simply to remove this special-casing: it turns out that the code in the "multiple UDFs" branch just so happens to work for the single-UDF case because Python treats `(x)` as equivalent to `x`, not as a single-argument tuple.

New regression test in `pyspark.python.sql.tests` module (tested and confirmed that it fails before my fix).

Author: Josh Rosen <joshrosen@databricks.com>

Closes apache#17927 from JoshRosen/SPARK-20685.

(cherry picked from commit 8ddbc43)
Signed-off-by: Xiao Li <gatorsmile@gmail.com>
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