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[GLUTEN-9382][VL]Support bucket write with non partition table #9575

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Merged
JkSelf merged 1 commit into from
Jun 5, 2025
Merged

[GLUTEN-9382][VL]Support bucket write with non partition table #9575

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2 changes: 1 addition & 1 deletion backends-velox/src/main/scala/org/apache/gluten/backendsapi/velox/VeloxBackend.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -351,7 +351,7 @@ object VeloxBackendSettings extends BackendSettingsApi {
// is limited to partitioned tables. Therefore, we should add this condition restriction.
// After velox supports bucketed non-partitioned tables, we can remove the restriction on
// partitioned tables.
if (bucketSpec.isEmpty || (isHiveCompatibleBucketTable && isPartitionedTable)) {
if (bucketSpec.isEmpty || isHiveCompatibleBucketTable) {
None
} else {
Some("Unsupported native write: non-compatible hive bucket write is not supported.")
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8 changes: 4 additions & 4 deletions ...s-velox/src/test/scala/org/apache/spark/sql/execution/VeloxParquetWriteForHiveSuite.scala
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Expand Up @@ -271,7 +271,7 @@ class VeloxParquetWriteForHiveSuite
}
}

test("bucket writer with non-dynamic partition should fallback") {
test("bucket writer with non-dynamic partition") {
if (isSparkVersionGE("3.4")) {
Seq("true", "false").foreach {
enableConvertMetastore =>
Expand All @@ -293,7 +293,7 @@ class VeloxParquetWriteForHiveSuite
// hive relation convert always use dynamic, so it will offload to native.
checkNativeWrite(
s"INSERT INTO $target PARTITION(k='0') SELECT i, j FROM $source",
checkNative = enableConvertMetastore.toBoolean)
checkNative = true)
val files = tableDir(target)
.listFiles()
.filterNot(f => f.getName.startsWith(".") || f.getName.startsWith("_"))
Expand All @@ -305,7 +305,7 @@ class VeloxParquetWriteForHiveSuite
}
}

test("bucket writer with non-partition table should fallback") {
test("bucket writer with non-partition table") {
if (isSparkVersionGE("3.4")) {
Seq("true", "false").foreach {
enableConvertMetastore =>
Expand All @@ -323,7 +323,7 @@ class VeloxParquetWriteForHiveSuite
(0 until 50).map(i => (i % 13, i.toString)).toDF("i", "j")
df.write.mode(SaveMode.Overwrite).saveAsTable(source)

checkNativeWrite(s"INSERT INTO $target SELECT i, j FROM $source", checkNative = false)
checkNativeWrite(s"INSERT INTO $target SELECT i, j FROM $source", checkNative = true)

checkAnswer(spark.table(target), df)
}
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