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[GitHub] [spark] AngersZhuuuu opened a new pull request #30839: [SPARK-33593][SQL] Vector reader got incorrect data with binary partition value
AngersZhuuuu opened a new pull request #30839:
URL: https://github.com/apache/spark/pull/30839
### What changes were proposed in this pull request?
Currently when enable parquet vectorized reader, use binary type as partition col will return incorrect value as below UT
```scala
test("Parquet vector reader incorrect with binary partition value") {
Seq(false, true).foreach(tag => {
withSQLConf("spark.sql.parquet.enableVectorizedReader" -> tag.toString) {
withTable("t1") {
sql(
"""CREATE TABLE t1(name STRING, id BINARY, part BINARY)
| USING PARQUET PARTITIONED BY (part)""".stripMargin)
sql(s"INSERT INTO t1 PARTITION(part = 'Spark SQL') VALUES('a', X'537061726B2053514C')")
if (tag) {
checkAnswer(sql("SELECT name, cast(id as string), cast(part as string) FROM t1"),
Row("a", "Spark SQL", ""))
} else {
checkAnswer(sql("SELECT name, cast(id as string), cast(part as string) FROM t1"),
Row("a", "Spark SQL", "Spark SQL"))
}
}
}
})
}
```
### Why are the changes needed?
Fix data incorrect issue
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Added UT
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[GitHub] [spark] AngersZhuuuu commented on pull request #30839: [SPARK-33593][SQL][FOLLOW-UP][3.0] Vector reader got incorrect data with binary partition value
Posted by GitBox <gi...@apache.org>.
AngersZhuuuu commented on pull request #30839:
URL: https://github.com/apache/spark/pull/30839#issuecomment-748110512
retest this please
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* This patch passes all tests.
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[GitHub] [spark] dongjoon-hyun closed pull request #30839: [SPARK-33593][SQL][3.0] Vector reader got incorrect data with binary partition value
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dongjoon-hyun closed pull request #30839:
URL: https://github.com/apache/spark/pull/30839
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* This patch **fails Spark unit tests**.
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