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[SPARK-23727][SQL] Support for pushing down filters for DateType in parquet #20851

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[SPARK-23727][SQL] Support for pushing down filters for DateType in parquet #20851

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079af71
[SPARK-23727][SQL] Support DATE predict push down in parquet
yucai Mar 18, 2018
59d8483
minor, code style
yucai Mar 18, 2018
1f2b450
Add spark.sql.parquet.filterPushdown.date
yucai Mar 18, 2018
4df29df
Make spark.sql.parquet.filterPushdown.date internal
yucai Mar 19, 2018
8f36d1e
Use DateTimeUtils.fromJavaDate
yucai Mar 19, 2018
82c5a73
code style
yucai Mar 20, 2018
784b625
Use 1.date instead of 1.d
yucai Mar 21, 2018
7946bea
Should respect session local timezone
yucai Mar 21, 2018
423a938
Make suite more readable
yucai Mar 22, 2018
a58eec8
code style
yucai Mar 22, 2018
b43e36c
minor
yucai Mar 22, 2018
b70def0
Set spark.sql.parquet.filterPushdown.date=true by default
yucai Mar 26, 2018
759f468
convert date without timezone
yucai Mar 29, 2018
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8 changes: 8 additions & 0 deletions sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -353,6 +353,12 @@ object SQLConf {
.booleanConf
.createWithDefault(true)

val PARQUET_FILTER_PUSHDOWN_DATE_ENABLED = buildConf("spark.sql.parquet.filterPushdown.date")
.doc("If true, enables Parquet filter push-down optimization for Date. " +
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@viirya viirya Mar 19, 2018

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Should be an internal conf, i.e., .internal()?

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@yucai yucai Mar 19, 2018

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@gatorsmile any idea?

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@gatorsmile gatorsmile Mar 23, 2018

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Yes, it should be an internal conf. In Spark 3.0 release, we will revisit all the internal confs and remove all the unnecessary confs.

"This configuration only has an effect when 'spark.sql.parquet.filterPushdown' is enabled.")
.booleanConf
.createWithDefault(true)
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@dongjoon-hyun dongjoon-hyun Mar 22, 2018

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For this kind of thing, we had better start with false.

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@HyukjinKwon HyukjinKwon Mar 22, 2018

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+1


val PARQUET_WRITE_LEGACY_FORMAT = buildConf("spark.sql.parquet.writeLegacyFormat")
.doc("Whether to be compatible with the legacy Parquet format adopted by Spark 1.4 and prior " +
"versions, when converting Parquet schema to Spark SQL schema and vice versa.")
Expand Down Expand Up @@ -1319,6 +1325,8 @@ class SQLConf extends Serializable with Logging {

def parquetFilterPushDown: Boolean = getConf(PARQUET_FILTER_PUSHDOWN_ENABLED)

def parquetFilterPushDownDate: Boolean = getConf(PARQUET_FILTER_PUSHDOWN_DATE_ENABLED)

def orcFilterPushDown: Boolean = getConf(ORC_FILTER_PUSHDOWN_ENABLED)

def verifyPartitionPath: Boolean = getConf(HIVE_VERIFY_PARTITION_PATH)
Expand Down
55 changes: 55 additions & 0 deletions ...re/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilters.scala
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Expand Up @@ -21,6 +21,7 @@ import org.apache.parquet.filter2.predicate._
import org.apache.parquet.filter2.predicate.FilterApi._
import org.apache.parquet.io.api.Binary

import org.apache.spark.sql.internal.SQLConf
import org.apache.spark.sql.sources
import org.apache.spark.sql.types._

Expand Down Expand Up @@ -50,6 +51,15 @@ private[parquet] object ParquetFilters {
(n: String, v: Any) => FilterApi.eq(
binaryColumn(n),
Option(v).map(b => Binary.fromReusedByteArray(v.asInstanceOf[Array[Byte]])).orNull)
case DateType if SQLConf.get.parquetFilterPushDownDate =>
(n: String, v: Any) => {
FilterApi.eq(
intColumn(n),
Option(v).map { date =>
val days = date.asInstanceOf[java.sql.Date].getTime / (24 * 60 * 60 * 1000)
days.toInt.asInstanceOf[Integer]
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@viirya viirya Mar 19, 2018

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Use DateTimeUtils.fromJavaDate here and below?

}.orNull)
}
}

private val makeNotEq: PartialFunction[DataType, (String, Any) => FilterPredicate] = {
Expand All @@ -72,6 +82,15 @@ private[parquet] object ParquetFilters {
(n: String, v: Any) => FilterApi.notEq(
binaryColumn(n),
Option(v).map(b => Binary.fromReusedByteArray(v.asInstanceOf[Array[Byte]])).orNull)
case DateType if SQLConf.get.parquetFilterPushDownDate =>
(n: String, v: Any) => {
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@HyukjinKwon HyukjinKwon Mar 20, 2018

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nit:

(n: String, v: Any) => FilterApi.notEq(
 intColumn(n),
 Option(v).map { d =>
   DateTimeUtils.fromJavaDate(d.asInstanceOf[java.sql.Date]).asInstanceOf[Integer]
 }.orNull)

FilterApi.notEq(
intColumn(n),
Option(v).map { date =>
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@ghost ghost Mar 19, 2018

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These 3 lines are repeated several times in this change. Please refactor to a new method.

val days = date.asInstanceOf[java.sql.Date].getTime / (24 * 60 * 60 * 1000)
days.toInt.asInstanceOf[Integer]
}.orNull)
}
}

private val makeLt: PartialFunction[DataType, (String, Any) => FilterPredicate] = {
Expand All @@ -91,6 +110,15 @@ private[parquet] object ParquetFilters {
case BinaryType =>
(n: String, v: Any) =>
FilterApi.lt(binaryColumn(n), Binary.fromReusedByteArray(v.asInstanceOf[Array[Byte]]))
case DateType if SQLConf.get.parquetFilterPushDownDate =>
(n: String, v: Any) => {
FilterApi.lt(
intColumn(n),
Option(v).map { date =>
val days = date.asInstanceOf[java.sql.Date].getTime / (24 * 60 * 60 * 1000)
days.toInt.asInstanceOf[Integer]
}.orNull)
}
}

private val makeLtEq: PartialFunction[DataType, (String, Any) => FilterPredicate] = {
Expand All @@ -110,6 +138,15 @@ private[parquet] object ParquetFilters {
case BinaryType =>
(n: String, v: Any) =>
FilterApi.ltEq(binaryColumn(n), Binary.fromReusedByteArray(v.asInstanceOf[Array[Byte]]))
case DateType if SQLConf.get.parquetFilterPushDownDate =>
(n: String, v: Any) => {
FilterApi.ltEq(
intColumn(n),
Option(v).map { date =>
val days = date.asInstanceOf[java.sql.Date].getTime / (24 * 60 * 60 * 1000)
days.toInt.asInstanceOf[Integer]
}.orNull)
}
}

private val makeGt: PartialFunction[DataType, (String, Any) => FilterPredicate] = {
Expand All @@ -129,6 +166,15 @@ private[parquet] object ParquetFilters {
case BinaryType =>
(n: String, v: Any) =>
FilterApi.gt(binaryColumn(n), Binary.fromReusedByteArray(v.asInstanceOf[Array[Byte]]))
case DateType if SQLConf.get.parquetFilterPushDownDate =>
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@cloud-fan cloud-fan Mar 26, 2018

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we should refactor it, so that adding a new data type doesn't need to touch so many places. This can be done later.

(n: String, v: Any) => {
FilterApi.gt(
intColumn(n),
Option(v).map { date =>
val days = date.asInstanceOf[java.sql.Date].getTime / (24 * 60 * 60 * 1000)
days.toInt.asInstanceOf[Integer]
}.orNull)
}
}

private val makeGtEq: PartialFunction[DataType, (String, Any) => FilterPredicate] = {
Expand All @@ -148,6 +194,15 @@ private[parquet] object ParquetFilters {
case BinaryType =>
(n: String, v: Any) =>
FilterApi.gtEq(binaryColumn(n), Binary.fromReusedByteArray(v.asInstanceOf[Array[Byte]]))
case DateType if SQLConf.get.parquetFilterPushDownDate =>
(n: String, v: Any) => {
FilterApi.gtEq(
intColumn(n),
Option(v).map { date =>
val days = date.asInstanceOf[java.sql.Date].getTime / (24 * 60 * 60 * 1000)
days.toInt.asInstanceOf[Integer]
}.orNull)
}
}

/**
Expand Down
35 changes: 34 additions & 1 deletion ...rc/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala
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Expand Up @@ -18,6 +18,7 @@
package org.apache.spark.sql.execution.datasources.parquet

import java.nio.charset.StandardCharsets
import java.sql.Date

import org.apache.parquet.filter2.predicate.{FilterPredicate, Operators}
import org.apache.parquet.filter2.predicate.FilterApi._
Expand Down Expand Up @@ -76,7 +77,9 @@ class ParquetFilterSuite extends QueryTest with ParquetTest with SharedSQLContex
expected: Seq[Row]): Unit = {
val output = predicate.collect { case a: Attribute => a }.distinct

withSQLConf(SQLConf.PARQUET_FILTER_PUSHDOWN_ENABLED.key -> "true") {
withSQLConf(
SQLConf.PARQUET_FILTER_PUSHDOWN_ENABLED.key -> "true",
SQLConf.PARQUET_FILTER_PUSHDOWN_DATE_ENABLED.key -> "true") {
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@HyukjinKwon HyukjinKwon Mar 20, 2018

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nit:

withSQLConf(
  SQLConf.PARQUET_FILTER_PUSHDOWN_ENABLED.key -> "true",
  SQLConf.PARQUET_FILTER_PUSHDOWN_DATE_ENABLED.key -> "true",
  SQLConf.PARQUET_VECTORIZED_READER_ENABLED.key -> "false") {

withSQLConf(SQLConf.PARQUET_VECTORIZED_READER_ENABLED.key -> "false") {
val query = df
.select(output.map(e => Column(e)): _*)
Expand Down Expand Up @@ -313,6 +316,36 @@ class ParquetFilterSuite extends QueryTest with ParquetTest with SharedSQLContex
}
}

test("filter pushdown - date") {
implicit class IntToDate(int: Int) {
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@HyukjinKwon HyukjinKwon Mar 20, 2018

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Shall we pass a string here and convert it into a date?

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@yucai yucai Mar 20, 2018

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How about this way? It is from ORC's date push down.

  test("filter pushdown - date") {
    val dates = Seq("2017-08-18", "2017-08-19", "2017-08-20", "2017-08-21").map { day =>
      Date.valueOf(day)
    }
    withOrcDataFrame(dates.map(Tuple1(_))) { implicit df =>
      checkFilterPredicate('_1.isNull, PredicateLeaf.Operator.IS_NULL)

      checkFilterPredicate('_1 === dates(0), PredicateLeaf.Operator.EQUALS)
      checkFilterPredicate('_1 <=> dates(0), PredicateLeaf.Operator.NULL_SAFE_EQUALS)

      checkFilterPredicate('_1 < dates(1), PredicateLeaf.Operator.LESS_THAN)
      checkFilterPredicate('_1 > dates(2), PredicateLeaf.Operator.LESS_THAN_EQUALS)
      checkFilterPredicate('_1 <= dates(0), PredicateLeaf.Operator.LESS_THAN_EQUALS)
      checkFilterPredicate('_1 >= dates(3), PredicateLeaf.Operator.LESS_THAN)

      checkFilterPredicate(Literal(dates(0)) === '_1, PredicateLeaf.Operator.EQUALS)
      checkFilterPredicate(Literal(dates(0)) <=> '_1, PredicateLeaf.Operator.NULL_SAFE_EQUALS)
      checkFilterPredicate(Literal(dates(1)) > '_1, PredicateLeaf.Operator.LESS_THAN)
      checkFilterPredicate(Literal(dates(2)) < '_1, PredicateLeaf.Operator.LESS_THAN_EQUALS)
      checkFilterPredicate(Literal(dates(0)) >= '_1, PredicateLeaf.Operator.LESS_THAN_EQUALS)
      checkFilterPredicate(Literal(dates(3)) <= '_1, PredicateLeaf.Operator.LESS_THAN)
    }
  }

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@HyukjinKwon HyukjinKwon Mar 20, 2018

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Either way looks fine but I usually stick to what other codes do around the fix though ..

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@yucai yucai Mar 20, 2018

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Ok, do you mean this way? Looks like we need more words :).

    implicit class StringToDate(s: String) {
      def d: Date = Date.valueOf(s)
    }

    withParquetDataFrame(
      Seq("2017-08-18", "2017-08-19", "2017-08-20", "2017-08-21").map(i => Tuple1(i.d))) {
        implicit df =>
          checkFilterPredicate('_1.isNull, classOf[Eq[_]], Seq.empty[Row])
          checkFilterPredicate('_1.isNotNull, classOf[NotEq[_]],
            Seq("2017-08-18", "2017-08-19", "2017-08-20", "2017-08-21").map(i => Row.apply(i.d)))

          checkFilterPredicate('_1 === "2017-08-18".d, classOf[Eq[_]], "2017-08-18".d)
          checkFilterPredicate('_1 =!= "2017-08-18".d, classOf[NotEq[_]],
            Seq("2017-08-19", "2017-08-20", "2017-08-21").map(i => Row.apply(i.d)))

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@HyukjinKwon HyukjinKwon Mar 21, 2018

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I think "2017-08-19".d is at least better than 1.d.

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@HyukjinKwon HyukjinKwon Mar 21, 2018

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Yup, I think this one is better than the current one.

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@yucai yucai Mar 21, 2018

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As per @cloud-fan 's suggestion, I have changed 1.d to 1.date, which one is perferred?

  1. "2017-08-18".d
  2. 1.date
  3. "2017-08-18".date

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@cloud-fan cloud-fan Mar 21, 2018

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the string one is more readable to me

def d: Date = new Date(Date.valueOf("2018-03-01").getTime + 24 * 60 * 60 * 1000 * (int - 1))
}

withParquetDataFrame((1 to 4).map(i => Tuple1(i.d))) { implicit df =>
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@gatorsmile gatorsmile Mar 18, 2018

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These test cases only cover the limited cases. We need to check the boundary values

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@yucai yucai Mar 18, 2018

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Could you kindly give me some examples about what kind of boundary tests? I checked parquet integer push down and ORC date type push down, seems like have covered all their tests.

checkFilterPredicate('_1.isNull, classOf[Eq[_]], Seq.empty[Row])
checkFilterPredicate('_1.isNotNull, classOf[NotEq[_]], (1 to 4).map(i => Row.apply(i.d)))

checkFilterPredicate('_1 === 1.d, classOf[Eq[_]], 1.d)
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@cloud-fan cloud-fan Mar 20, 2018

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1.d is weird, can we name it 1.date?

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@yucai yucai Mar 21, 2018 •
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I agree 1.date is better, but binary is using "1.b", shall we keep the same pattern with it?

  test("filter pushdown - binary") {
    implicit class IntToBinary(int: Int) {
      def b: Array[Byte] = int.toString.getBytes(StandardCharsets.UTF_8)
    }

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@cloud-fan cloud-fan Mar 21, 2018

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b might be OK, but d is confusing as it's also a postfix for double.

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@yucai yucai Mar 21, 2018

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Got it, thanks very much for explanation.

checkFilterPredicate('_1 <=> 1.d, classOf[Eq[_]], 1.d)
checkFilterPredicate('_1 =!= 1.d, classOf[NotEq[_]], (2 to 4).map(i => Row.apply(i.d)))

checkFilterPredicate('_1 < 2.d, classOf[Lt[_]], 1.d)
checkFilterPredicate('_1 > 3.d, classOf[Gt[_]], 4.d)
checkFilterPredicate('_1 <= 1.d, classOf[LtEq[_]], 1.d)
checkFilterPredicate('_1 >= 4.d, classOf[GtEq[_]], 4.d)

checkFilterPredicate(Literal(1.d) === '_1, classOf[Eq[_]], 1.d)
checkFilterPredicate(Literal(1.d) <=> '_1, classOf[Eq[_]], 1.d)
checkFilterPredicate(Literal(2.d) > '_1, classOf[Lt[_]], 1.d)
checkFilterPredicate(Literal(3.d) < '_1, classOf[Gt[_]], 4.d)
checkFilterPredicate(Literal(1.d) >= '_1, classOf[LtEq[_]], 1.d)
checkFilterPredicate(Literal(4.d) <= '_1, classOf[GtEq[_]], 4.d)

checkFilterPredicate(!('_1 < 4.d), classOf[GtEq[_]], 4.d)
checkFilterPredicate('_1 < 2.d || '_1 > 3.d, classOf[Operators.Or], Seq(Row(1.d), Row(4.d)))
}
}

test("SPARK-6554: don't push down predicates which reference partition columns") {
import testImplicits._

Expand Down