sunchao opened a new pull request #33330:
URL: https://github.com/apache/spark/pull/33330
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### What changes were proposed in this pull request?
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Fix the skipping values logic in Parquet vectorized reader when column index
is effective, by considering nulls. Also refactored `ParquetColumnIndexSuite`
to allow sharing more code.
### Why are the changes needed?
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Currently, the Parquet vectorized reader may not work correctly if column
index filtering is effective, and the data page contains null values. For
instance, let's say we have two columns `c1: BIGINT` and `c2: STRING`, and the
following pages:
```
* c1 500 500 500 500
* |---------|---------|---------|---------|
* |-------|-----|-----|---|---|---|---|---|
* c2 400 300 200 200 200 200 200 200
```
and suppose we have a query like the following:
```sql
SELECT * FROM t WHERE c1 = 500
```
this will create a Parquet row range `[500, 1000)` which, when applied to
`c2`, will require us to skip all the rows in `[400,500)`. However the current
logic for skipping rows is via `updater.skipValues(n, valueReader)` which is
incorrect since this skips the next `n` non-null values. In the case when nulls
are present, this will not work correctly.
### Does this PR introduce _any_ user-facing change?
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No
### How was this patch tested?
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Added a new test in `ParquetColumnIndexSuite`.
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