Repository: spark Updated Branches: refs/heads/master 8aceb961c -> 43e4e851b
[SPARK-24718][SQL] Timestamp support pushdown to parquet data source ## What changes were proposed in this pull request? `Timestamp` support pushdown to parquet data source. Only `TIMESTAMP_MICROS` and `TIMESTAMP_MILLIS` support push down. ## How was this patch tested? unit tests and benchmark tests Author: Yuming Wang <yumw...@ebay.com> Closes #21741 from wangyum/SPARK-24718. Project: http://git-wip-us.apache.org/repos/asf/spark/repo Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/43e4e851 Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/43e4e851 Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/43e4e851 Branch: refs/heads/master Commit: 43e4e851b642bbee535d22e1b9e72ec6b99f6ed4 Parents: 8aceb96 Author: Yuming Wang <yumw...@ebay.com> Authored: Sun Jul 15 11:13:49 2018 +0800 Committer: hyukjinkwon <gurwls...@apache.org> Committed: Sun Jul 15 11:13:49 2018 +0800 ---------------------------------------------------------------------- .../org/apache/spark/sql/internal/SQLConf.scala | 11 ++ .../FilterPushdownBenchmark-results.txt | 124 +++++++++++++++++++ .../datasources/parquet/ParquetFileFormat.scala | 3 +- .../datasources/parquet/ParquetFilters.scala | 59 ++++++++- .../benchmark/FilterPushdownBenchmark.scala | 37 +++++- .../parquet/ParquetFilterSuite.scala | 74 ++++++++++- 6 files changed, 301 insertions(+), 7 deletions(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/spark/blob/43e4e851/sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala ---------------------------------------------------------------------- diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala index 699e939..07d33fa 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala @@ -378,6 +378,15 @@ object SQLConf { .booleanConf .createWithDefault(true) + val PARQUET_FILTER_PUSHDOWN_TIMESTAMP_ENABLED = + buildConf("spark.sql.parquet.filterPushdown.timestamp") + .doc("If true, enables Parquet filter push-down optimization for Timestamp. " + + "This configuration only has an effect when 'spark.sql.parquet.filterPushdown' is " + + "enabled and Timestamp stored as TIMESTAMP_MICROS or TIMESTAMP_MILLIS type.") + .internal() + .booleanConf + .createWithDefault(true) + val PARQUET_FILTER_PUSHDOWN_STRING_STARTSWITH_ENABLED = buildConf("spark.sql.parquet.filterPushdown.string.startsWith") .doc("If true, enables Parquet filter push-down optimization for string startsWith function. " + @@ -1494,6 +1503,8 @@ class SQLConf extends Serializable with Logging { def parquetFilterPushDownDate: Boolean = getConf(PARQUET_FILTER_PUSHDOWN_DATE_ENABLED) + def parquetFilterPushDownTimestamp: Boolean = getConf(PARQUET_FILTER_PUSHDOWN_TIMESTAMP_ENABLED) + def parquetFilterPushDownStringStartWith: Boolean = getConf(PARQUET_FILTER_PUSHDOWN_STRING_STARTSWITH_ENABLED) http://git-wip-us.apache.org/repos/asf/spark/blob/43e4e851/sql/core/benchmarks/FilterPushdownBenchmark-results.txt ---------------------------------------------------------------------- diff --git a/sql/core/benchmarks/FilterPushdownBenchmark-results.txt b/sql/core/benchmarks/FilterPushdownBenchmark-results.txt index c44908b..4f38cc4 100644 --- a/sql/core/benchmarks/FilterPushdownBenchmark-results.txt +++ b/sql/core/benchmarks/FilterPushdownBenchmark-results.txt @@ -578,3 +578,127 @@ Native ORC Vectorized 11622 / 12196 1.4 7 Native ORC Vectorized (Pushdown) 11377 / 11654 1.4 723.3 1.0X +================================================================================================ +Pushdown benchmark for Timestamp +================================================================================================ + +Java HotSpot(TM) 64-Bit Server VM 1.8.0_151-b12 on Mac OS X 10.12.6 +Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz + +Select 1 timestamp stored as INT96 row (value = CAST(7864320 AS timestamp)): Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative +------------------------------------------------------------------------------------------------ +Parquet Vectorized 4784 / 4956 3.3 304.2 1.0X +Parquet Vectorized (Pushdown) 4838 / 4917 3.3 307.6 1.0X +Native ORC Vectorized 3923 / 4173 4.0 249.4 1.2X +Native ORC Vectorized (Pushdown) 894 / 943 17.6 56.8 5.4X + +Java HotSpot(TM) 64-Bit Server VM 1.8.0_151-b12 on Mac OS X 10.12.6 +Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz + +Select 10% timestamp stored as INT96 rows (value < CAST(1572864 AS timestamp)): Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative +------------------------------------------------------------------------------------------------ +Parquet Vectorized 5686 / 5901 2.8 361.5 1.0X +Parquet Vectorized (Pushdown) 5555 / 5895 2.8 353.2 1.0X +Native ORC Vectorized 4844 / 4957 3.2 308.0 1.2X +Native ORC Vectorized (Pushdown) 2141 / 2230 7.3 136.1 2.7X + +Java HotSpot(TM) 64-Bit Server VM 1.8.0_151-b12 on Mac OS X 10.12.6 +Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz + +Select 50% timestamp stored as INT96 rows (value < CAST(7864320 AS timestamp)): Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative +------------------------------------------------------------------------------------------------ +Parquet Vectorized 9100 / 9421 1.7 578.6 1.0X +Parquet Vectorized (Pushdown) 9122 / 9496 1.7 580.0 1.0X +Native ORC Vectorized 8365 / 8874 1.9 531.9 1.1X +Native ORC Vectorized (Pushdown) 7128 / 7376 2.2 453.2 1.3X + +Java HotSpot(TM) 64-Bit Server VM 1.8.0_151-b12 on Mac OS X 10.12.6 +Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz + +Select 90% timestamp stored as INT96 rows (value < CAST(14155776 AS timestamp)): Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative +------------------------------------------------------------------------------------------------ +Parquet Vectorized 12764 / 13120 1.2 811.5 1.0X +Parquet Vectorized (Pushdown) 12656 / 13003 1.2 804.7 1.0X +Native ORC Vectorized 13096 / 13233 1.2 832.6 1.0X +Native ORC Vectorized (Pushdown) 12710 / 15611 1.2 808.1 1.0X + +Java HotSpot(TM) 64-Bit Server VM 1.8.0_151-b12 on Mac OS X 10.12.6 +Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz + +Select 1 timestamp stored as TIMESTAMP_MICROS row (value = CAST(7864320 AS timestamp)): Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative +------------------------------------------------------------------------------------------------ +Parquet Vectorized 4381 / 4796 3.6 278.5 1.0X +Parquet Vectorized (Pushdown) 122 / 137 129.3 7.7 36.0X +Native ORC Vectorized 3913 / 3988 4.0 248.8 1.1X +Native ORC Vectorized (Pushdown) 905 / 945 17.4 57.6 4.8X + +Java HotSpot(TM) 64-Bit Server VM 1.8.0_151-b12 on Mac OS X 10.12.6 +Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz + +Select 10% timestamp stored as TIMESTAMP_MICROS rows (value < CAST(1572864 AS timestamp)): Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative +------------------------------------------------------------------------------------------------ +Parquet Vectorized 5145 / 5184 3.1 327.1 1.0X +Parquet Vectorized (Pushdown) 1426 / 1519 11.0 90.7 3.6X +Native ORC Vectorized 4827 / 4901 3.3 306.9 1.1X +Native ORC Vectorized (Pushdown) 2133 / 2210 7.4 135.6 2.4X + +Java HotSpot(TM) 64-Bit Server VM 1.8.0_151-b12 on Mac OS X 10.12.6 +Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz + +Select 50% timestamp stored as TIMESTAMP_MICROS rows (value < CAST(7864320 AS timestamp)): Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative +------------------------------------------------------------------------------------------------ +Parquet Vectorized 9234 / 9516 1.7 587.1 1.0X +Parquet Vectorized (Pushdown) 6752 / 7046 2.3 429.3 1.4X +Native ORC Vectorized 8418 / 8998 1.9 535.2 1.1X +Native ORC Vectorized (Pushdown) 7199 / 7314 2.2 457.7 1.3X + +Java HotSpot(TM) 64-Bit Server VM 1.8.0_151-b12 on Mac OS X 10.12.6 +Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz + +Select 90% timestamp stored as TIMESTAMP_MICROS rows (value < CAST(14155776 AS timestamp)): Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative +------------------------------------------------------------------------------------------------ +Parquet Vectorized 12414 / 12458 1.3 789.2 1.0X +Parquet Vectorized (Pushdown) 12094 / 12249 1.3 768.9 1.0X +Native ORC Vectorized 12198 / 13755 1.3 775.5 1.0X +Native ORC Vectorized (Pushdown) 12205 / 12431 1.3 776.0 1.0X + +Java HotSpot(TM) 64-Bit Server VM 1.8.0_151-b12 on Mac OS X 10.12.6 +Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz + +Select 1 timestamp stored as TIMESTAMP_MILLIS row (value = CAST(7864320 AS timestamp)): Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative +------------------------------------------------------------------------------------------------ +Parquet Vectorized 4369 / 4515 3.6 277.8 1.0X +Parquet Vectorized (Pushdown) 116 / 125 136.2 7.3 37.8X +Native ORC Vectorized 3965 / 4703 4.0 252.1 1.1X +Native ORC Vectorized (Pushdown) 892 / 1162 17.6 56.7 4.9X + +Java HotSpot(TM) 64-Bit Server VM 1.8.0_151-b12 on Mac OS X 10.12.6 +Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz + +Select 10% timestamp stored as TIMESTAMP_MILLIS rows (value < CAST(1572864 AS timestamp)): Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative +------------------------------------------------------------------------------------------------ +Parquet Vectorized 5211 / 5409 3.0 331.3 1.0X +Parquet Vectorized (Pushdown) 1427 / 1438 11.0 90.7 3.7X +Native ORC Vectorized 4719 / 4883 3.3 300.1 1.1X +Native ORC Vectorized (Pushdown) 2191 / 2228 7.2 139.3 2.4X + +Java HotSpot(TM) 64-Bit Server VM 1.8.0_151-b12 on Mac OS X 10.12.6 +Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz + +Select 50% timestamp stored as TIMESTAMP_MILLIS rows (value < CAST(7864320 AS timestamp)): Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative +------------------------------------------------------------------------------------------------ +Parquet Vectorized 8716 / 8953 1.8 554.2 1.0X +Parquet Vectorized (Pushdown) 6632 / 6968 2.4 421.7 1.3X +Native ORC Vectorized 8376 / 9118 1.9 532.5 1.0X +Native ORC Vectorized (Pushdown) 7218 / 7609 2.2 458.9 1.2X + +Java HotSpot(TM) 64-Bit Server VM 1.8.0_151-b12 on Mac OS X 10.12.6 +Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz + +Select 90% timestamp stored as TIMESTAMP_MILLIS rows (value < CAST(14155776 AS timestamp)): Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative +------------------------------------------------------------------------------------------------ +Parquet Vectorized 12264 / 12452 1.3 779.7 1.0X +Parquet Vectorized (Pushdown) 11766 / 11927 1.3 748.0 1.0X +Native ORC Vectorized 12101 / 12301 1.3 769.3 1.0X +Native ORC Vectorized (Pushdown) 11983 / 12651 1.3 761.9 1.0X + http://git-wip-us.apache.org/repos/asf/spark/blob/43e4e851/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFileFormat.scala ---------------------------------------------------------------------- diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFileFormat.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFileFormat.scala index efddf8d..3ec33b2 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFileFormat.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFileFormat.scala @@ -341,6 +341,7 @@ class ParquetFileFormat // Whole stage codegen (PhysicalRDD) is able to deal with batches directly val returningBatch = supportBatch(sparkSession, resultSchema) val pushDownDate = sqlConf.parquetFilterPushDownDate + val pushDownTimestamp = sqlConf.parquetFilterPushDownTimestamp val pushDownStringStartWith = sqlConf.parquetFilterPushDownStringStartWith val pushDownInFilterThreshold = sqlConf.parquetFilterPushDownInFilterThreshold @@ -366,7 +367,7 @@ class ParquetFileFormat val pushed = if (enableParquetFilterPushDown) { val parquetSchema = ParquetFileReader.readFooter(sharedConf, filePath, SKIP_ROW_GROUPS) .getFileMetaData.getSchema - val parquetFilters = new ParquetFilters(pushDownDate, + val parquetFilters = new ParquetFilters(pushDownDate, pushDownTimestamp, pushDownStringStartWith, pushDownInFilterThreshold) filters // Collects all converted Parquet filter predicates. Notice that not all predicates can be http://git-wip-us.apache.org/repos/asf/spark/blob/43e4e851/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilters.scala ---------------------------------------------------------------------- diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilters.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilters.scala index e590c15..0c146f2 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilters.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilters.scala @@ -17,14 +17,15 @@ package org.apache.spark.sql.execution.datasources.parquet -import java.sql.Date +import java.lang.{Long => JLong} +import java.sql.{Date, Timestamp} import scala.collection.JavaConverters.asScalaBufferConverter import org.apache.parquet.filter2.predicate._ import org.apache.parquet.filter2.predicate.FilterApi._ import org.apache.parquet.io.api.Binary -import org.apache.parquet.schema.{DecimalMetadata, MessageType, OriginalType, PrimitiveComparator, PrimitiveType} +import org.apache.parquet.schema.{DecimalMetadata, MessageType, OriginalType, PrimitiveComparator} import org.apache.parquet.schema.OriginalType._ import org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName import org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName._ @@ -39,6 +40,7 @@ import org.apache.spark.unsafe.types.UTF8String */ private[parquet] class ParquetFilters( pushDownDate: Boolean, + pushDownTimestamp: Boolean, pushDownStartWith: Boolean, pushDownInFilterThreshold: Int) { @@ -57,6 +59,8 @@ private[parquet] class ParquetFilters( private val ParquetStringType = ParquetSchemaType(UTF8, BINARY, null) private val ParquetBinaryType = ParquetSchemaType(null, BINARY, null) private val ParquetDateType = ParquetSchemaType(DATE, INT32, null) + private val ParquetTimestampMicrosType = ParquetSchemaType(TIMESTAMP_MICROS, INT64, null) + private val ParquetTimestampMillisType = ParquetSchemaType(TIMESTAMP_MILLIS, INT64, null) private def dateToDays(date: Date): SQLDate = { DateTimeUtils.fromJavaDate(date) @@ -89,6 +93,15 @@ private[parquet] class ParquetFilters( (n: String, v: Any) => FilterApi.eq( intColumn(n), Option(v).map(date => dateToDays(date.asInstanceOf[Date]).asInstanceOf[Integer]).orNull) + case ParquetTimestampMicrosType if pushDownTimestamp => + (n: String, v: Any) => FilterApi.eq( + longColumn(n), + Option(v).map(t => DateTimeUtils.fromJavaTimestamp(t.asInstanceOf[Timestamp]) + .asInstanceOf[JLong]).orNull) + case ParquetTimestampMillisType if pushDownTimestamp => + (n: String, v: Any) => FilterApi.eq( + longColumn(n), + Option(v).map(_.asInstanceOf[Timestamp].getTime.asInstanceOf[JLong]).orNull) } private val makeNotEq: PartialFunction[ParquetSchemaType, (String, Any) => FilterPredicate] = { @@ -117,6 +130,15 @@ private[parquet] class ParquetFilters( (n: String, v: Any) => FilterApi.notEq( intColumn(n), Option(v).map(date => dateToDays(date.asInstanceOf[Date]).asInstanceOf[Integer]).orNull) + case ParquetTimestampMicrosType if pushDownTimestamp => + (n: String, v: Any) => FilterApi.notEq( + longColumn(n), + Option(v).map(t => DateTimeUtils.fromJavaTimestamp(t.asInstanceOf[Timestamp]) + .asInstanceOf[JLong]).orNull) + case ParquetTimestampMillisType if pushDownTimestamp => + (n: String, v: Any) => FilterApi.notEq( + longColumn(n), + Option(v).map(_.asInstanceOf[Timestamp].getTime.asInstanceOf[JLong]).orNull) } private val makeLt: PartialFunction[ParquetSchemaType, (String, Any) => FilterPredicate] = { @@ -139,6 +161,14 @@ private[parquet] class ParquetFilters( case ParquetDateType if pushDownDate => (n: String, v: Any) => FilterApi.lt(intColumn(n), dateToDays(v.asInstanceOf[Date]).asInstanceOf[Integer]) + case ParquetTimestampMicrosType if pushDownTimestamp => + (n: String, v: Any) => FilterApi.lt( + longColumn(n), + DateTimeUtils.fromJavaTimestamp(v.asInstanceOf[Timestamp]).asInstanceOf[JLong]) + case ParquetTimestampMillisType if pushDownTimestamp => + (n: String, v: Any) => FilterApi.lt( + longColumn(n), + v.asInstanceOf[Timestamp].getTime.asInstanceOf[JLong]) } private val makeLtEq: PartialFunction[ParquetSchemaType, (String, Any) => FilterPredicate] = { @@ -161,6 +191,14 @@ private[parquet] class ParquetFilters( case ParquetDateType if pushDownDate => (n: String, v: Any) => FilterApi.ltEq(intColumn(n), dateToDays(v.asInstanceOf[Date]).asInstanceOf[Integer]) + case ParquetTimestampMicrosType if pushDownTimestamp => + (n: String, v: Any) => FilterApi.ltEq( + longColumn(n), + DateTimeUtils.fromJavaTimestamp(v.asInstanceOf[Timestamp]).asInstanceOf[JLong]) + case ParquetTimestampMillisType if pushDownTimestamp => + (n: String, v: Any) => FilterApi.ltEq( + longColumn(n), + v.asInstanceOf[Timestamp].getTime.asInstanceOf[JLong]) } private val makeGt: PartialFunction[ParquetSchemaType, (String, Any) => FilterPredicate] = { @@ -183,6 +221,14 @@ private[parquet] class ParquetFilters( case ParquetDateType if pushDownDate => (n: String, v: Any) => FilterApi.gt(intColumn(n), dateToDays(v.asInstanceOf[Date]).asInstanceOf[Integer]) + case ParquetTimestampMicrosType if pushDownTimestamp => + (n: String, v: Any) => FilterApi.gt( + longColumn(n), + DateTimeUtils.fromJavaTimestamp(v.asInstanceOf[Timestamp]).asInstanceOf[JLong]) + case ParquetTimestampMillisType if pushDownTimestamp => + (n: String, v: Any) => FilterApi.gt( + longColumn(n), + v.asInstanceOf[Timestamp].getTime.asInstanceOf[JLong]) } private val makeGtEq: PartialFunction[ParquetSchemaType, (String, Any) => FilterPredicate] = { @@ -205,6 +251,14 @@ private[parquet] class ParquetFilters( case ParquetDateType if pushDownDate => (n: String, v: Any) => FilterApi.gtEq(intColumn(n), dateToDays(v.asInstanceOf[Date]).asInstanceOf[Integer]) + case ParquetTimestampMicrosType if pushDownTimestamp => + (n: String, v: Any) => FilterApi.gtEq( + longColumn(n), + DateTimeUtils.fromJavaTimestamp(v.asInstanceOf[Timestamp]).asInstanceOf[JLong]) + case ParquetTimestampMillisType if pushDownTimestamp => + (n: String, v: Any) => FilterApi.gtEq( + longColumn(n), + v.asInstanceOf[Timestamp].getTime.asInstanceOf[JLong]) } /** @@ -241,6 +295,7 @@ private[parquet] class ParquetFilters( | ParquetLongType | ParquetFloatType | ParquetDoubleType | ParquetStringType | ParquetBinaryType => true case ParquetDateType if pushDownDate => true + case ParquetTimestampMicrosType | ParquetTimestampMillisType if pushDownTimestamp => true case _ => false } http://git-wip-us.apache.org/repos/asf/spark/blob/43e4e851/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/FilterPushdownBenchmark.scala ---------------------------------------------------------------------- diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/FilterPushdownBenchmark.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/FilterPushdownBenchmark.scala index fc716de..567a8eb 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/FilterPushdownBenchmark.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/FilterPushdownBenchmark.scala @@ -28,7 +28,8 @@ import org.apache.spark.SparkFunSuite import org.apache.spark.sql.{DataFrame, SparkSession} import org.apache.spark.sql.functions.monotonically_increasing_id import org.apache.spark.sql.internal.SQLConf -import org.apache.spark.sql.types.{ByteType, Decimal, DecimalType} +import org.apache.spark.sql.internal.SQLConf.ParquetOutputTimestampType +import org.apache.spark.sql.types.{ByteType, Decimal, DecimalType, TimestampType} import org.apache.spark.util.{Benchmark, Utils} /** @@ -359,6 +360,40 @@ class FilterPushdownBenchmark extends SparkFunSuite with BenchmarkBeforeAndAfter } } } + + ignore(s"Pushdown benchmark for Timestamp") { + withTempPath { dir => + withSQLConf(SQLConf.PARQUET_FILTER_PUSHDOWN_TIMESTAMP_ENABLED.key -> true.toString) { + ParquetOutputTimestampType.values.toSeq.map(_.toString).foreach { fileType => + withSQLConf(SQLConf.PARQUET_OUTPUT_TIMESTAMP_TYPE.key -> fileType) { + val columns = (1 to width).map(i => s"CAST(id AS string) c$i") + val df = spark.range(numRows).selectExpr(columns: _*) + .withColumn("value", monotonically_increasing_id().cast(TimestampType)) + withTempTable("orcTable", "patquetTable") { + saveAsTable(df, dir) + + Seq(s"value = CAST($mid AS timestamp)").foreach { whereExpr => + val title = s"Select 1 timestamp stored as $fileType row ($whereExpr)" + .replace("value AND value", "value") + filterPushDownBenchmark(numRows, title, whereExpr) + } + + val selectExpr = (1 to width).map(i => s"MAX(c$i)").mkString("", ",", ", MAX(value)") + Seq(10, 50, 90).foreach { percent => + filterPushDownBenchmark( + numRows, + s"Select $percent% timestamp stored as $fileType rows " + + s"(value < CAST(${numRows * percent / 100} AS timestamp))", + s"value < CAST(${numRows * percent / 100} as timestamp)", + selectExpr + ) + } + } + } + } + } + } + } } trait BenchmarkBeforeAndAfterEachTest extends BeforeAndAfterEachTestData { this: Suite => http://git-wip-us.apache.org/repos/asf/spark/blob/43e4e851/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala ---------------------------------------------------------------------- diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala index 00c191f..924f136 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala @@ -18,7 +18,7 @@ package org.apache.spark.sql.execution.datasources.parquet import java.nio.charset.StandardCharsets -import java.sql.Date +import java.sql.{Date, Timestamp} import org.apache.parquet.filter2.predicate.{FilterApi, FilterPredicate, Operators} import org.apache.parquet.filter2.predicate.FilterApi._ @@ -31,6 +31,7 @@ import org.apache.spark.sql.catalyst.planning.PhysicalOperation import org.apache.spark.sql.execution.datasources.{DataSourceStrategy, HadoopFsRelation, LogicalRelation} import org.apache.spark.sql.functions._ import org.apache.spark.sql.internal.SQLConf +import org.apache.spark.sql.internal.SQLConf.ParquetOutputTimestampType import org.apache.spark.sql.test.SharedSQLContext import org.apache.spark.sql.types._ import org.apache.spark.util.{AccumulatorContext, AccumulatorV2} @@ -56,8 +57,8 @@ import org.apache.spark.util.{AccumulatorContext, AccumulatorV2} class ParquetFilterSuite extends QueryTest with ParquetTest with SharedSQLContext { private lazy val parquetFilters = - new ParquetFilters(conf.parquetFilterPushDownDate, conf.parquetFilterPushDownStringStartWith, - conf.parquetFilterPushDownInFilterThreshold) + new ParquetFilters(conf.parquetFilterPushDownDate, conf.parquetFilterPushDownTimestamp, + conf.parquetFilterPushDownStringStartWith, conf.parquetFilterPushDownInFilterThreshold) override def beforeEach(): Unit = { super.beforeEach() @@ -84,6 +85,7 @@ class ParquetFilterSuite extends QueryTest with ParquetTest with SharedSQLContex withSQLConf( SQLConf.PARQUET_FILTER_PUSHDOWN_ENABLED.key -> "true", SQLConf.PARQUET_FILTER_PUSHDOWN_DATE_ENABLED.key -> "true", + SQLConf.PARQUET_FILTER_PUSHDOWN_TIMESTAMP_ENABLED.key -> "true", SQLConf.PARQUET_FILTER_PUSHDOWN_STRING_STARTSWITH_ENABLED.key -> "true", SQLConf.PARQUET_VECTORIZED_READER_ENABLED.key -> "false") { val query = df @@ -144,6 +146,39 @@ class ParquetFilterSuite extends QueryTest with ParquetTest with SharedSQLContex checkBinaryFilterPredicate(predicate, filterClass, Seq(Row(expected)))(df) } + private def testTimestampPushdown(data: Seq[Timestamp]): Unit = { + assert(data.size === 4) + val ts1 = data.head + val ts2 = data(1) + val ts3 = data(2) + val ts4 = data(3) + + withParquetDataFrame(data.map(i => Tuple1(i))) { implicit df => + checkFilterPredicate('_1.isNull, classOf[Eq[_]], Seq.empty[Row]) + checkFilterPredicate('_1.isNotNull, classOf[NotEq[_]], data.map(i => Row.apply(i))) + + checkFilterPredicate('_1 === ts1, classOf[Eq[_]], ts1) + checkFilterPredicate('_1 <=> ts1, classOf[Eq[_]], ts1) + checkFilterPredicate('_1 =!= ts1, classOf[NotEq[_]], + Seq(ts2, ts3, ts4).map(i => Row.apply(i))) + + checkFilterPredicate('_1 < ts2, classOf[Lt[_]], ts1) + checkFilterPredicate('_1 > ts1, classOf[Gt[_]], Seq(ts2, ts3, ts4).map(i => Row.apply(i))) + checkFilterPredicate('_1 <= ts1, classOf[LtEq[_]], ts1) + checkFilterPredicate('_1 >= ts4, classOf[GtEq[_]], ts4) + + checkFilterPredicate(Literal(ts1) === '_1, classOf[Eq[_]], ts1) + checkFilterPredicate(Literal(ts1) <=> '_1, classOf[Eq[_]], ts1) + checkFilterPredicate(Literal(ts2) > '_1, classOf[Lt[_]], ts1) + checkFilterPredicate(Literal(ts3) < '_1, classOf[Gt[_]], ts4) + checkFilterPredicate(Literal(ts1) >= '_1, classOf[LtEq[_]], ts1) + checkFilterPredicate(Literal(ts4) <= '_1, classOf[GtEq[_]], ts4) + + checkFilterPredicate(!('_1 < ts4), classOf[GtEq[_]], ts4) + checkFilterPredicate('_1 < ts2 || '_1 > ts3, classOf[Operators.Or], Seq(Row(ts1), Row(ts4))) + } + } + // This function tests that exactly go through the `canDrop` and `inverseCanDrop`. private def testStringStartsWith(dataFrame: DataFrame, filter: String): Unit = { withTempPath { dir => @@ -444,6 +479,39 @@ class ParquetFilterSuite extends QueryTest with ParquetTest with SharedSQLContex } } + test("filter pushdown - timestamp") { + // spark.sql.parquet.outputTimestampType = TIMESTAMP_MILLIS + val millisData = Seq(Timestamp.valueOf("2018-06-14 08:28:53.123"), + Timestamp.valueOf("2018-06-15 08:28:53.123"), + Timestamp.valueOf("2018-06-16 08:28:53.123"), + Timestamp.valueOf("2018-06-17 08:28:53.123")) + withSQLConf(SQLConf.PARQUET_OUTPUT_TIMESTAMP_TYPE.key -> + ParquetOutputTimestampType.TIMESTAMP_MILLIS.toString) { + testTimestampPushdown(millisData) + } + + // spark.sql.parquet.outputTimestampType = TIMESTAMP_MICROS + val microsData = Seq(Timestamp.valueOf("2018-06-14 08:28:53.123456"), + Timestamp.valueOf("2018-06-15 08:28:53.123456"), + Timestamp.valueOf("2018-06-16 08:28:53.123456"), + Timestamp.valueOf("2018-06-17 08:28:53.123456")) + withSQLConf(SQLConf.PARQUET_OUTPUT_TIMESTAMP_TYPE.key -> + ParquetOutputTimestampType.TIMESTAMP_MICROS.toString) { + testTimestampPushdown(microsData) + } + + // spark.sql.parquet.outputTimestampType = INT96 doesn't support pushdown + withSQLConf(SQLConf.PARQUET_OUTPUT_TIMESTAMP_TYPE.key -> + ParquetOutputTimestampType.INT96.toString) { + withParquetDataFrame(millisData.map(i => Tuple1(i))) { implicit df => + assertResult(None) { + parquetFilters.createFilter( + new SparkToParquetSchemaConverter(conf).convert(df.schema), sources.IsNull("_1")) + } + } + } + } + test("SPARK-6554: don't push down predicates which reference partition columns") { import testImplicits._ --------------------------------------------------------------------- To unsubscribe, e-mail: commits-unsubscr...@spark.apache.org For additional commands, e-mail: commits-h...@spark.apache.org
