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JVM columnar shuffle panics on a struct column with a NullType field

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Assessment

Difficulty
2/5
Estimated time
1-3 hours
Newbie friendliness
72/100
Issue type
Bug
Clarity
Clearly specified
Activity status
Active
Tech stack
java, rust
Domain
data-engineering

Research direction

Start in native/shuffle/src/spark_unsafe/row.rs at the two field-major functions, append_struct_fields_field_major and append_nested_struct_fields_field_major, which reach unreachable! for DataType::Null. Compare with the existing Null arm in append_field in the same file to see how a per-row null is appended. Done when the three SQL repros in the issue return Spark's rows, with a regression test covering a top-level and a nested struct with a null field.

Written by the indexing model from the issue text.

Description

area:shuffle bug priority:high requires-triage
Describe the bug

A shuffle that runs on Comet's JVM columnar shuffle fails the query when one of its columns is a struct with a NullType field, such as named_struct('x', a, 'n', null). The row-to-Arrow conversion panics:

org.apache.comet.CometNativeException: internal error: entered unreachable code: Unsupported data type of struct field: Null
        at datafusion_comet_shuffle::spark_unsafe::row::append_struct_fields_field_major
        at datafusion_comet_shuffle::spark_unsafe::row::append_columns
        at datafusion_comet_shuffle::spark_unsafe::row::process_sorted_row_partition
        at comet::execution::jni_api::write_sorted_file
        at comet::execution::jni_api::Java_org_apache_comet_Native_writeSortedFileNative

Spark returns the rows. Both field-major struct paths in native/shuffle/src/spark_unsafe/row.rs lack a DataType::Null arm and fall through to unreachable!. append_struct_fields_field_major handles a top-level struct column, and append_nested_struct_fields_field_major handles a struct inside a struct:

https://github.com/apache/datafusion-comet/blob/3a4a15940983e4bb9a9a74c816ee51e2cf6d9e17/native/shuffle/src/spark_unsafe/row.rs#L1042-L1047

https://github.com/apache/datafusion-comet/blob/3a4a15940983e4bb9a9a74c816ee51e2cf6d9e17/native/shuffle/src/spark_unsafe/row.rs#L582-L587

append_field in the same file already has the arm. The JVM columnar shuffle's type check accepts NullType at any depth, so nothing keeps these schemas away from the converter, and Null is the only type that check accepts that the two functions are missing.

https://github.com/apache/datafusion-comet/blob/3a4a15940983e4bb9a9a74c816ee51e2cf6d9e17/native/shuffle/src/spark_unsafe/row.rs#L272-L275

With the default configuration this hits every round-robin repartition of such a column, because native round robin is off by default and those shuffles run on JVM columnar shuffle. It also hits a hash shuffle that runs on JVM columnar shuffle, for example under spark.comet.shuffle.mode=jvm. A hash shuffle over a native child runs on native shuffle and works. Arrays and maps that hold nulls (array(null), map(k, null), array(named_struct('x', a, 'n', null))) also work.

Steps to reproduce
CREATE TABLE t (a INT) USING parquet;
INSERT INTO t SELECT CAST(id AS INT) FROM range(1000);

-- top-level struct column
SELECT /*+ REPARTITION(4) */ a, named_struct('x', a, 'n', null) AS st FROM t;

-- struct inside a struct
SELECT /*+ REPARTITION(4) */ a, named_struct('s', named_struct('x', a, 'n', null)) AS st FROM t;

-- hash partitioning on JVM columnar shuffle
SET spark.comet.shuffle.mode=jvm;
SELECT a, named_struct('x', a, 'n', null) AS st FROM t DISTRIBUTE BY a;

All three fail with the panic above. I reproduced them on c3316fbe39 with the Spark 4.1 profile, and the code involved is unchanged on main at 3a4a159409.

Expected behavior

The queries should return the same rows as Spark. Every value of a NullType field is null, so a DataType::Null arm in both functions that appends one null per row, as append_field does, should be enough. A regression test with a top-level and a nested struct would cover both paths.

Additional context

#6977 proposes merging the two field-major functions, which would make an arm like this one change instead of two.

Dominant language
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