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[SPARK-25579][SQL] Use quoted attribute names if needed in pushed ORC predicates #22597

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[SPARK-25579][SQL] Use quoted attribute names if needed in pushed ORC predicates #22597

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[SPARK-25579][SQL] Use quoted attribute names if needed in pushed ORC…
dongjoon-hyun Oct 1, 2018
335a39f
Add a test case.
dongjoon-hyun Oct 13, 2018
849c7fa
Add withSQLConf with ORC_FILTER_PUSHDOWN_ENABLED=true
dongjoon-hyun Oct 14, 2018
7686179
Address comments
dongjoon-hyun Oct 16, 2018
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37 changes: 28 additions & 9 deletions sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/orc/OrcFilters.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -67,6 +67,16 @@ private[sql] object OrcFilters {
}
}

// Since ORC 1.5.0 (ORC-323), we need to quote for column names with `.` characters
// in order to distinguish predicate pushdown for nested columns.
private def quoteAttributeNameIfNeeded(name: String) : String = {
if (!name.contains("`") && name.contains(".")) {
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@HyukjinKwon HyukjinKwon Oct 1, 2018

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Does this condition take the backtick in column name into account? For instance,

>>> spark.range(1).toDF("abc`.abc").show()
+--------+
|abc`.abc|
+--------+
|       0|
+--------+

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@dongjoon-hyun dongjoon-hyun Oct 1, 2018

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Thank you for review. I'll consider that, too.

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@dongjoon-hyun dongjoon-hyun Oct 13, 2018

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@HyukjinKwon . Actually, Spark 2.3.2 ORC (native/hive) doesn't support a backtick character in column names. It fails on writing operation. And, although Spark 2.4.0 broadens the supported special characters like . and " in column names, the backtick character is not handled yet.

So, for that one, I'll proceed in another PR since it's an improvement instead of a regression.

Also, cc @gatorsmile and @dbtsai .

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@dongjoon-hyun dongjoon-hyun Oct 13, 2018

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For ORC and AVRO improvement, SPARK-25722 is created.

s"`$name`"
} else {
name
}
}

/**
* Create ORC filter as a SearchArgument instance.
*/
Expand Down Expand Up @@ -178,38 +188,47 @@ private[sql] object OrcFilters {
// wrapped by a "parent" predicate (`And`, `Or`, or `Not`).

case EqualTo(attribute, value) if isSearchableType(dataTypeMap(attribute)) =>
val quotedName = quoteAttributeNameIfNeeded(attribute)
val castedValue = castLiteralValue(value, dataTypeMap(attribute))
Some(builder.startAnd().equals(attribute, getType(attribute), castedValue).end())
Some(builder.startAnd().equals(quotedName, getType(attribute), castedValue).end())

case EqualNullSafe(attribute, value) if isSearchableType(dataTypeMap(attribute)) =>
val quotedName = quoteAttributeNameIfNeeded(attribute)
val castedValue = castLiteralValue(value, dataTypeMap(attribute))
Some(builder.startAnd().nullSafeEquals(attribute, getType(attribute), castedValue).end())
Some(builder.startAnd().nullSafeEquals(quotedName, getType(attribute), castedValue).end())

case LessThan(attribute, value) if isSearchableType(dataTypeMap(attribute)) =>
val quotedName = quoteAttributeNameIfNeeded(attribute)
val castedValue = castLiteralValue(value, dataTypeMap(attribute))
Some(builder.startAnd().lessThan(attribute, getType(attribute), castedValue).end())
Some(builder.startAnd().lessThan(quotedName, getType(attribute), castedValue).end())

case LessThanOrEqual(attribute, value) if isSearchableType(dataTypeMap(attribute)) =>
val quotedName = quoteAttributeNameIfNeeded(attribute)
val castedValue = castLiteralValue(value, dataTypeMap(attribute))
Some(builder.startAnd().lessThanEquals(attribute, getType(attribute), castedValue).end())
Some(builder.startAnd().lessThanEquals(quotedName, getType(attribute), castedValue).end())

case GreaterThan(attribute, value) if isSearchableType(dataTypeMap(attribute)) =>
val quotedName = quoteAttributeNameIfNeeded(attribute)
val castedValue = castLiteralValue(value, dataTypeMap(attribute))
Some(builder.startNot().lessThanEquals(attribute, getType(attribute), castedValue).end())
Some(builder.startNot().lessThanEquals(quotedName, getType(attribute), castedValue).end())

case GreaterThanOrEqual(attribute, value) if isSearchableType(dataTypeMap(attribute)) =>
val quotedName = quoteAttributeNameIfNeeded(attribute)
val castedValue = castLiteralValue(value, dataTypeMap(attribute))
Some(builder.startNot().lessThan(attribute, getType(attribute), castedValue).end())
Some(builder.startNot().lessThan(quotedName, getType(attribute), castedValue).end())

case IsNull(attribute) if isSearchableType(dataTypeMap(attribute)) =>
Some(builder.startAnd().isNull(attribute, getType(attribute)).end())
val quotedName = quoteAttributeNameIfNeeded(attribute)
Some(builder.startAnd().isNull(quotedName, getType(attribute)).end())

case IsNotNull(attribute) if isSearchableType(dataTypeMap(attribute)) =>
Some(builder.startNot().isNull(attribute, getType(attribute)).end())
val quotedName = quoteAttributeNameIfNeeded(attribute)
Some(builder.startNot().isNull(quotedName, getType(attribute)).end())

case In(attribute, values) if isSearchableType(dataTypeMap(attribute)) =>
val quotedName = quoteAttributeNameIfNeeded(attribute)
val castedValues = values.map(v => castLiteralValue(v, dataTypeMap(attribute)))
Some(builder.startAnd().in(attribute, getType(attribute),
Some(builder.startAnd().in(quotedName, getType(attribute),
castedValues.map(_.asInstanceOf[AnyRef]): _*).end())

case _ => None
Expand Down
28 changes: 8 additions & 20 deletions sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/orc/OrcQuerySuite.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -445,16 +445,7 @@ abstract class OrcQueryTest extends OrcTest {
test("Support for pushing down filters for decimal types") {
withSQLConf(SQLConf.ORC_FILTER_PUSHDOWN_ENABLED.key -> "true") {
val data = (0 until 10).map(i => Tuple1(BigDecimal.valueOf(i)))
withTempPath { file =>
// It needs to repartition data so that we can have several ORC files
// in order to skip stripes in ORC.
spark.createDataFrame(data).toDF("a").repartition(10)
.write.orc(file.getCanonicalPath)
val df = spark.read.orc(file.getCanonicalPath).where("a == 2")
val actual = stripSparkFilter(df).count()

assert(actual < 10)
}
checkPredicatePushDown(spark.createDataFrame(data).toDF("a"), 10, "a == 2")
}
}

Expand All @@ -465,16 +456,7 @@ abstract class OrcQueryTest extends OrcTest {
val milliseconds = Timestamp.valueOf(timeString).getTime + i * 3600
Tuple1(new Timestamp(milliseconds))
}
withTempPath { file =>
// It needs to repartition data so that we can have several ORC files
// in order to skip stripes in ORC.
spark.createDataFrame(data).toDF("a").repartition(10)
.write.orc(file.getCanonicalPath)
val df = spark.read.orc(file.getCanonicalPath).where(s"a == '$timeString'")
val actual = stripSparkFilter(df).count()

assert(actual < 10)
}
checkPredicatePushDown(spark.createDataFrame(data).toDF("a"), 10, s"a == '$timeString'")
}
}

Expand Down Expand Up @@ -674,6 +656,12 @@ class OrcQuerySuite extends OrcQueryTest with SharedSQLContext {
}
}

test("SPARK-25579 ORC PPD should support column names with dot") {
withSQLConf(SQLConf.ORC_FILTER_PUSHDOWN_ENABLED.key -> "true") {
checkPredicatePushDown(spark.range(10).toDF("col.dot"), 10, "`col.dot` == 2")
}
}

test("SPARK-20728 Make ORCFileFormat configurable between sql/hive and sql/core") {
withSQLConf(SQLConf.ORC_IMPLEMENTATION.key -> "hive") {
val e = intercept[AnalysisException] {
Expand Down
10 changes: 10 additions & 0 deletions sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/orc/OrcTest.scala
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Expand Up @@ -106,4 +106,14 @@ abstract class OrcTest extends QueryTest with SQLTestUtils with BeforeAndAfterAl
df: DataFrame, path: File): Unit = {
df.write.mode(SaveMode.Overwrite).orc(path.getCanonicalPath)
}

protected def checkPredicatePushDown(df: DataFrame, numRows: Int, predicate: String): Unit = {
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@dongjoon-hyun dongjoon-hyun Oct 16, 2018 •
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@HyukjinKwon . I refactor this since it's repeated three times now.
And, this function should be here because the existing two instances are in OrcQueryTest and new instance is in OrcQuerySuite. There is another similar instance, but I skipped it because it's not the same pattern.

withTempPath { file =>
// It needs to repartition data so that we can have several ORC files
// in order to skip stripes in ORC.
df.repartition(numRows).write.orc(file.getCanonicalPath)
val actual = stripSparkFilter(spark.read.orc(file.getCanonicalPath).where(predicate)).count()
assert(actual < numRows)
}
}
}