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[SPARK-20685] Fix BatchPythonEvaluation bug in case of single UDF w/ repeated arg. #17927
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Test build #76707 has finished for PR 17927 at commit
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gatorsmile
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May 10, 2017
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LGTM
Thanks! Merging to master/2.2/2.1 |
asfgit
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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
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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>
liyichao
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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
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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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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 tox
, 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).