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[HUDI-3739] Fix handling of the isNotNull predicate in Data Skipping (#5224)

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- Fix handling of the isNotNull predicate in Data Skipping
This commit is contained in:
Alexey Kudinkin
2022-04-06 12:17:36 -07:00
committed by GitHub
parent b2f09a1fee
commit d43b4cd95e
8 changed files with 214 additions and 208 deletions
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38
hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/hudi/ColumnStatsIndexSupport.scala
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@@ -54,7 +54,8 @@ trait ColumnStatsIndexSupport extends SparkAdapterSupport {
HoodieMetadataPayload.COLUMN_STATS_FIELD_FILE_NAME, HoodieMetadataPayload.COLUMN_STATS_FIELD_FILE_NAME,
HoodieMetadataPayload.COLUMN_STATS_FIELD_MIN_VALUE, HoodieMetadataPayload.COLUMN_STATS_FIELD_MIN_VALUE,
HoodieMetadataPayload.COLUMN_STATS_FIELD_MAX_VALUE, HoodieMetadataPayload.COLUMN_STATS_FIELD_MAX_VALUE,
HoodieMetadataPayload.COLUMN_STATS_FIELD_NULL_COUNT) HoodieMetadataPayload.COLUMN_STATS_FIELD_NULL_COUNT,
HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_COUNT)
val requiredMetadataIndexColumns = val requiredMetadataIndexColumns =
(targetColStatsIndexColumns :+ HoodieMetadataPayload.COLUMN_STATS_FIELD_COLUMN_NAME).map(colName => (targetColStatsIndexColumns :+ HoodieMetadataPayload.COLUMN_STATS_FIELD_COLUMN_NAME).map(colName =>
@@ -98,7 +99,7 @@ trait ColumnStatsIndexSupport extends SparkAdapterSupport {
* *
* <pre> * <pre>
* +---------------------------+------------+------------+-------------+ * +---------------------------+------------+------------+-------------+
* | file | A_minValue | A_maxValue | A_num_nulls | * | file | A_minValue | A_maxValue | A_nullCount |
* +---------------------------+------------+------------+-------------+ * +---------------------------+------------+------------+-------------+
* | one_base_file.parquet | 1 | 10 | 0 | * | one_base_file.parquet | 1 | 10 | 0 |
* | another_base_file.parquet | -10 | 0 | 5 | * | another_base_file.parquet | -10 | 0 | 5 |
@@ -133,6 +134,7 @@ trait ColumnStatsIndexSupport extends SparkAdapterSupport {
val maxValueOrdinal = colStatsSchemaOrdinalsMap(HoodieMetadataPayload.COLUMN_STATS_FIELD_MAX_VALUE) val maxValueOrdinal = colStatsSchemaOrdinalsMap(HoodieMetadataPayload.COLUMN_STATS_FIELD_MAX_VALUE)
val fileNameOrdinal = colStatsSchemaOrdinalsMap(HoodieMetadataPayload.COLUMN_STATS_FIELD_FILE_NAME) val fileNameOrdinal = colStatsSchemaOrdinalsMap(HoodieMetadataPayload.COLUMN_STATS_FIELD_FILE_NAME)
val nullCountOrdinal = colStatsSchemaOrdinalsMap(HoodieMetadataPayload.COLUMN_STATS_FIELD_NULL_COUNT) val nullCountOrdinal = colStatsSchemaOrdinalsMap(HoodieMetadataPayload.COLUMN_STATS_FIELD_NULL_COUNT)
val valueCountOrdinal = colStatsSchemaOrdinalsMap(HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_COUNT)
val transposedRDD = colStatsDF.rdd val transposedRDD = colStatsDF.rdd
.filter(row => sortedColumns.contains(row.getString(colNameOrdinal))) .filter(row => sortedColumns.contains(row.getString(colNameOrdinal)))
@@ -155,11 +157,13 @@ trait ColumnStatsIndexSupport extends SparkAdapterSupport {
case (_, columnRows) => case (_, columnRows) =>
// Rows seq is always non-empty (otherwise it won't be grouped into) // Rows seq is always non-empty (otherwise it won't be grouped into)
val fileName = columnRows.head.get(fileNameOrdinal) val fileName = columnRows.head.get(fileNameOrdinal)
val valueCount = columnRows.head.get(valueCountOrdinal)
val coalescedRowValuesSeq = columnRows.toSeq val coalescedRowValuesSeq = columnRows.toSeq
// NOTE: It's crucial to maintain appropriate ordering of the columns // NOTE: It's crucial to maintain appropriate ordering of the columns
// matching table layout // matching table layout
.sortBy(_.getString(colNameOrdinal)) .sortBy(_.getString(colNameOrdinal))
.foldLeft(Seq[Any](fileName)) { .foldLeft(Seq[Any](fileName, valueCount)) {
case (acc, columnRow) => case (acc, columnRow) =>
acc ++ Seq(minValueOrdinal, maxValueOrdinal, nullCountOrdinal).map(ord => columnRow.get(ord)) acc ++ Seq(minValueOrdinal, maxValueOrdinal, nullCountOrdinal).map(ord => columnRow.get(ord))
} }
@@ -223,11 +227,6 @@ trait ColumnStatsIndexSupport extends SparkAdapterSupport {
object ColumnStatsIndexSupport { object ColumnStatsIndexSupport {
private val COLUMN_STATS_INDEX_FILE_COLUMN_NAME = "fileName"
private val COLUMN_STATS_INDEX_MIN_VALUE_STAT_NAME = "minValue"
private val COLUMN_STATS_INDEX_MAX_VALUE_STAT_NAME = "maxValue"
private val COLUMN_STATS_INDEX_NUM_NULLS_STAT_NAME = "num_nulls"
private val metadataRecordSchemaString: String = HoodieMetadataRecord.SCHEMA$.toString private val metadataRecordSchemaString: String = HoodieMetadataRecord.SCHEMA$.toString
private val metadataRecordStructType: StructType = AvroConversionUtils.convertAvroSchemaToStructType(HoodieMetadataRecord.SCHEMA$) private val metadataRecordStructType: StructType = AvroConversionUtils.convertAvroSchemaToStructType(HoodieMetadataRecord.SCHEMA$)
@@ -235,28 +234,33 @@ object ColumnStatsIndexSupport {
* @VisibleForTesting * @VisibleForTesting
*/ */
def composeIndexSchema(targetColumnNames: Seq[String], tableSchema: StructType): StructType = { def composeIndexSchema(targetColumnNames: Seq[String], tableSchema: StructType): StructType = {
val fileNameField = StructField(COLUMN_STATS_INDEX_FILE_COLUMN_NAME, StringType, nullable = true, Metadata.empty) val fileNameField = StructField(HoodieMetadataPayload.COLUMN_STATS_FIELD_FILE_NAME, StringType, nullable = true, Metadata.empty)
val valueCountField = StructField(HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_COUNT, LongType, nullable = true, Metadata.empty)
val targetFields = targetColumnNames.map(colName => tableSchema.fields.find(f => f.name == colName).get) val targetFields = targetColumnNames.map(colName => tableSchema.fields.find(f => f.name == colName).get)
StructType( StructType(
targetFields.foldLeft(Seq(fileNameField)) { targetFields.foldLeft(Seq(fileNameField, valueCountField)) {
case (acc, field) => case (acc, field) =>
acc ++ Seq( acc ++ Seq(
composeColumnStatStructType(field.name, COLUMN_STATS_INDEX_MIN_VALUE_STAT_NAME, field.dataType), composeColumnStatStructType(field.name, HoodieMetadataPayload.COLUMN_STATS_FIELD_MIN_VALUE, field.dataType),
composeColumnStatStructType(field.name, COLUMN_STATS_INDEX_MAX_VALUE_STAT_NAME, field.dataType), composeColumnStatStructType(field.name, HoodieMetadataPayload.COLUMN_STATS_FIELD_MAX_VALUE, field.dataType),
composeColumnStatStructType(field.name, COLUMN_STATS_INDEX_NUM_NULLS_STAT_NAME, LongType)) composeColumnStatStructType(field.name, HoodieMetadataPayload.COLUMN_STATS_FIELD_NULL_COUNT, LongType))
} }
) )
} }
@inline def getMinColumnNameFor(colName: String): String = @inline def getMinColumnNameFor(colName: String): String =
formatColName(colName, COLUMN_STATS_INDEX_MIN_VALUE_STAT_NAME) formatColName(colName, HoodieMetadataPayload.COLUMN_STATS_FIELD_MIN_VALUE)
@inline def getMaxColumnNameFor(colName: String): String = @inline def getMaxColumnNameFor(colName: String): String =
formatColName(colName, COLUMN_STATS_INDEX_MAX_VALUE_STAT_NAME) formatColName(colName, HoodieMetadataPayload.COLUMN_STATS_FIELD_MAX_VALUE)
@inline def getNumNullsColumnNameFor(colName: String): String = @inline def getNullCountColumnNameFor(colName: String): String =
formatColName(colName, COLUMN_STATS_INDEX_NUM_NULLS_STAT_NAME) formatColName(colName, HoodieMetadataPayload.COLUMN_STATS_FIELD_NULL_COUNT)
@inline def getValueCountColumnNameFor: String =
HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_COUNT
@inline private def formatColName(col: String, statName: String) = { // TODO add escaping for @inline private def formatColName(col: String, statName: String) = { // TODO add escaping for
String.format("%s_%s", col, statName) String.format("%s_%s", col, statName)

7
hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/hudi/HoodieFileIndex.scala
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@@ -26,12 +26,13 @@ import org.apache.hudi.common.util.StringUtils
import org.apache.hudi.exception.HoodieException import org.apache.hudi.exception.HoodieException
import org.apache.hudi.keygen.constant.KeyGeneratorOptions import org.apache.hudi.keygen.constant.KeyGeneratorOptions
import org.apache.hudi.keygen.{TimestampBasedAvroKeyGenerator, TimestampBasedKeyGenerator} import org.apache.hudi.keygen.{TimestampBasedAvroKeyGenerator, TimestampBasedKeyGenerator}
import org.apache.hudi.metadata.{HoodieMetadataPayload, HoodieTableMetadata, HoodieTableMetadataUtil, MetadataPartitionType} import org.apache.hudi.metadata.{HoodieMetadataPayload, HoodieTableMetadataUtil}
import org.apache.spark.internal.Logging import org.apache.spark.internal.Logging
import org.apache.spark.sql.catalyst.InternalRow import org.apache.spark.sql.catalyst.InternalRow
import org.apache.spark.sql.catalyst.expressions.{And, Expression, Literal} import org.apache.spark.sql.catalyst.expressions.{And, Expression, Literal}
import org.apache.spark.sql.execution.datasources.{FileIndex, FileStatusCache, NoopCache, PartitionDirectory} import org.apache.spark.sql.execution.datasources.{FileIndex, FileStatusCache, NoopCache, PartitionDirectory}
import org.apache.spark.sql.hudi.{DataSkippingUtils, HoodieSqlCommonUtils} import org.apache.spark.sql.hudi.DataSkippingUtils.translateIntoColumnStatsIndexFilterExpr
import org.apache.spark.sql.hudi.HoodieSqlCommonUtils
import org.apache.spark.sql.internal.SQLConf import org.apache.spark.sql.internal.SQLConf
import org.apache.spark.sql.types._ import org.apache.spark.sql.types._
import org.apache.spark.sql.{Column, DataFrame, SparkSession} import org.apache.spark.sql.{Column, DataFrame, SparkSession}
@@ -211,7 +212,7 @@ case class HoodieFileIndex(spark: SparkSession,
withPersistence(transposedColStatsDF) { withPersistence(transposedColStatsDF) {
val indexSchema = transposedColStatsDF.schema val indexSchema = transposedColStatsDF.schema
val indexFilter = val indexFilter =
queryFilters.map(DataSkippingUtils.translateIntoColumnStatsIndexFilterExpr(_, indexSchema)) queryFilters.map(translateIntoColumnStatsIndexFilterExpr(_, indexSchema))
.reduce(And) .reduce(And)
val allIndexedFileNames = val allIndexedFileNames =

30
hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/spark/sql/hudi/DataSkippingUtils.scala
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@@ -17,7 +17,7 @@
package org.apache.spark.sql.hudi package org.apache.spark.sql.hudi
import org.apache.hudi.ColumnStatsIndexSupport.{getMaxColumnNameFor, getMinColumnNameFor, getNumNullsColumnNameFor} import org.apache.hudi.ColumnStatsIndexSupport.{getMaxColumnNameFor, getMinColumnNameFor, getNullCountColumnNameFor, getValueCountColumnNameFor}
import org.apache.hudi.SparkAdapterSupport import org.apache.hudi.SparkAdapterSupport
import org.apache.hudi.common.util.ValidationUtils.checkState import org.apache.hudi.common.util.ValidationUtils.checkState
import org.apache.spark.internal.Logging import org.apache.spark.internal.Logging
@@ -135,7 +135,7 @@ object DataSkippingUtils extends Logging {
} }
// Filter "colA = null" // Filter "colA = null"
// Translates to "colA_num_nulls = null" for index lookup // Translates to "colA_nullCount = null" for index lookup
case EqualNullSafe(attrRef: AttributeReference, litNull @ Literal(null, _)) => case EqualNullSafe(attrRef: AttributeReference, litNull @ Literal(null, _)) =>
getTargetIndexedColumnName(attrRef, indexSchema) getTargetIndexedColumnName(attrRef, indexSchema)
.map(colName => EqualTo(genColNumNullsExpr(colName), litNull)) .map(colName => EqualTo(genColNumNullsExpr(colName), litNull))
@@ -205,16 +205,16 @@ object DataSkippingUtils extends Logging {
} }
// Filter "colA is null" // Filter "colA is null"
// Translates to "colA_num_nulls > 0" for index lookup // Translates to "colA_nullCount > 0" for index lookup
case IsNull(attribute: AttributeReference) => case IsNull(attribute: AttributeReference) =>
getTargetIndexedColumnName(attribute, indexSchema) getTargetIndexedColumnName(attribute, indexSchema)
.map(colName => GreaterThan(genColNumNullsExpr(colName), Literal(0))) .map(colName => GreaterThan(genColNumNullsExpr(colName), Literal(0)))
// Filter "colA is not null" // Filter "colA is not null"
// Translates to "colA_num_nulls = 0" for index lookup // Translates to "colA_nullCount < colA_valueCount" for index lookup
case IsNotNull(attribute: AttributeReference) => case IsNotNull(attribute: AttributeReference) =>
getTargetIndexedColumnName(attribute, indexSchema) getTargetIndexedColumnName(attribute, indexSchema)
.map(colName => EqualTo(genColNumNullsExpr(colName), Literal(0))) .map(colName => LessThan(genColNumNullsExpr(colName), genColValueCountExpr))
// Filter "expr(colA) in (B1, B2, ...)" // Filter "expr(colA) in (B1, B2, ...)"
// Translates to "(colA_minValue <= B1 AND colA_maxValue >= B1) OR (colA_minValue <= B2 AND colA_maxValue >= B2) ... " // Translates to "(colA_minValue <= B1 AND colA_maxValue >= B1) OR (colA_minValue <= B2 AND colA_maxValue >= B2) ... "
@@ -294,7 +294,7 @@ object DataSkippingUtils extends Logging {
Set.apply( Set.apply(
getMinColumnNameFor(colName), getMinColumnNameFor(colName),
getMaxColumnNameFor(colName), getMaxColumnNameFor(colName),
getNumNullsColumnNameFor(colName) getNullCountColumnNameFor(colName)
) )
.forall(stat => indexSchema.exists(_.name == stat)) .forall(stat => indexSchema.exists(_.name == stat))
} }
@@ -325,19 +325,14 @@ object DataSkippingUtils extends Logging {
private object ColumnStatsExpressionUtils { private object ColumnStatsExpressionUtils {
def genColMinValueExpr(colName: String): Expression = @inline def genColMinValueExpr(colName: String): Expression = col(getMinColumnNameFor(colName)).expr
col(getMinColumnNameFor(colName)).expr @inline def genColMaxValueExpr(colName: String): Expression = col(getMaxColumnNameFor(colName)).expr
def genColMaxValueExpr(colName: String): Expression = @inline def genColNumNullsExpr(colName: String): Expression = col(getNullCountColumnNameFor(colName)).expr
col(getMaxColumnNameFor(colName)).expr @inline def genColValueCountExpr: Expression = col(getValueCountColumnNameFor).expr
def genColNumNullsExpr(colName: String): Expression =
col(getNumNullsColumnNameFor(colName)).expr
def genColumnValuesEqualToExpression(colName: String, @inline def genColumnValuesEqualToExpression(colName: String,
value: Expression, value: Expression,
targetExprBuilder: Function[Expression, Expression] = Predef.identity): Expression = { targetExprBuilder: Function[Expression, Expression] = Predef.identity): Expression = {
// TODO clean up
checkState(isValueExpression(value))
val minValueExpr = targetExprBuilder.apply(genColMinValueExpr(colName)) val minValueExpr = targetExprBuilder.apply(genColMinValueExpr(colName))
val maxValueExpr = targetExprBuilder.apply(genColMaxValueExpr(colName)) val maxValueExpr = targetExprBuilder.apply(genColMaxValueExpr(colName))
// Only case when column C contains value V is when min(C) <= V <= max(c) // Only case when column C contains value V is when min(C) <= V <= max(c)
@@ -347,9 +342,6 @@ private object ColumnStatsExpressionUtils {
def genColumnOnlyValuesEqualToExpression(colName: String, def genColumnOnlyValuesEqualToExpression(colName: String,
value: Expression, value: Expression,
targetExprBuilder: Function[Expression, Expression] = Predef.identity): Expression = { targetExprBuilder: Function[Expression, Expression] = Predef.identity): Expression = {
// TODO clean up
checkState(isValueExpression(value))
val minValueExpr = targetExprBuilder.apply(genColMinValueExpr(colName)) val minValueExpr = targetExprBuilder.apply(genColMinValueExpr(colName))
val maxValueExpr = targetExprBuilder.apply(genColMaxValueExpr(colName)) val maxValueExpr = targetExprBuilder.apply(genColMaxValueExpr(colName))
// Only case when column C contains _only_ value V is when min(C) = V AND max(c) = V // Only case when column C contains _only_ value V is when min(C) = V AND max(c) = V

2
hudi-spark-datasource/hudi-spark/src/test/java/org/apache/hudi/ColumnStatsIndexHelper.java
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@@ -130,7 +130,7 @@ public class ColumnStatsIndexHelper {
* *
* <pre> * <pre>
* +---------------------------+------------+------------+-------------+ * +---------------------------+------------+------------+-------------+
* | file | A_minValue | A_maxValue | A_num_nulls | * | file | A_minValue | A_maxValue | A_nullCount |
* +---------------------------+------------+------------+-------------+ * +---------------------------+------------+------------+-------------+
* | one_base_file.parquet | 1 | 10 | 0 | * | one_base_file.parquet | 1 | 10 | 0 |
* | another_base_file.parquet | -10 | 0 | 5 | * | another_base_file.parquet | -10 | 0 | 5 |

8
hudi-spark-datasource/hudi-spark/src/test/resources/index/zorder/column-stats-index-table.json
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@@ -1,4 +1,4 @@
{"c1_maxValue":769,"c1_minValue":309,"c1_num_nulls":0,"c2_maxValue":" 769sdc","c2_minValue":" 309sdc","c2_num_nulls":0,"c3_maxValue":919.769,"c3_minValue":76.430,"c3_num_nulls":0,"c4_maxValue":"2021-11-19T20:40:55.543-08:00","c4_minValue":"2021-11-19T20:40:55.521-08:00","c4_num_nulls":0,"c5_maxValue":78,"c5_minValue":32,"c5_num_nulls":0,"c6_maxValue":"2020-11-14","c6_minValue":"2020-01-08","c6_num_nulls":0,"c7_maxValue":"uQ==","c7_minValue":"AQ==","c7_num_nulls":0,"c8_maxValue":9,"c8_minValue":9,"c8_num_nulls":0} {"c1_maxValue":769,"c1_minValue":309,"c1_nullCount":0,"c2_maxValue":" 769sdc","c2_minValue":" 309sdc","c2_nullCount":0,"c3_maxValue":919.769,"c3_minValue":76.430,"c3_nullCount":0,"c4_maxValue":"2021-11-19T20:40:55.543-08:00","c4_minValue":"2021-11-19T20:40:55.521-08:00","c4_nullCount":0,"c5_maxValue":78,"c5_minValue":32,"c5_nullCount":0,"c6_maxValue":"2020-11-14","c6_minValue":"2020-01-08","c6_nullCount":0,"c7_maxValue":"uQ==","c7_minValue":"AQ==","c7_nullCount":0,"c8_maxValue":9,"c8_minValue":9,"c8_nullCount":0,"valueCount":9}
{"c1_maxValue":932,"c1_minValue":0,"c1_num_nulls":0,"c2_maxValue":" 932sdc","c2_minValue":" 0sdc","c2_num_nulls":0,"c3_maxValue":994.355,"c3_minValue":19.000,"c3_num_nulls":0,"c4_maxValue":"2021-11-19T20:40:55.549-08:00","c4_minValue":"2021-11-19T20:40:55.339-08:00","c4_num_nulls":0,"c5_maxValue":94,"c5_minValue":1,"c5_num_nulls":0,"c6_maxValue":"2020-09-09","c6_minValue":"2020-01-01","c6_num_nulls":0,"c7_maxValue":"xw==","c7_minValue":"AA==","c7_num_nulls":0,"c8_maxValue":9,"c8_minValue":9,"c8_num_nulls":0} {"c1_maxValue":932,"c1_minValue":0,"c1_nullCount":0,"c2_maxValue":" 932sdc","c2_minValue":" 0sdc","c2_nullCount":0,"c3_maxValue":994.355,"c3_minValue":19.000,"c3_nullCount":0,"c4_maxValue":"2021-11-19T20:40:55.549-08:00","c4_minValue":"2021-11-19T20:40:55.339-08:00","c4_nullCount":0,"c5_maxValue":94,"c5_minValue":1,"c5_nullCount":0,"c6_maxValue":"2020-09-09","c6_minValue":"2020-01-01","c6_nullCount":0,"c7_maxValue":"xw==","c7_minValue":"AA==","c7_nullCount":0,"c8_maxValue":9,"c8_minValue":9,"c8_nullCount":0,"valueCount":8}
{"c1_maxValue":943,"c1_minValue":89,"c1_num_nulls":0,"c2_maxValue":" 943sdc","c2_minValue":" 200sdc","c2_num_nulls":0,"c3_maxValue":854.690,"c3_minValue":100.556,"c3_num_nulls":0,"c4_maxValue":"2021-11-19T20:40:55.549-08:00","c4_minValue":"2021-11-19T20:40:55.508-08:00","c4_num_nulls":0,"c5_maxValue":95,"c5_minValue":10,"c5_num_nulls":0,"c6_maxValue":"2020-10-10","c6_minValue":"2020-01-10","c6_num_nulls":0,"c7_maxValue":"yA==","c7_minValue":"LA==","c7_num_nulls":0,"c8_maxValue":9,"c8_minValue":9,"c8_num_nulls":0} {"c1_maxValue":943,"c1_minValue":89,"c1_nullCount":0,"c2_maxValue":" 943sdc","c2_minValue":" 200sdc","c2_nullCount":0,"c3_maxValue":854.690,"c3_minValue":100.556,"c3_nullCount":0,"c4_maxValue":"2021-11-19T20:40:55.549-08:00","c4_minValue":"2021-11-19T20:40:55.508-08:00","c4_nullCount":0,"c5_maxValue":95,"c5_minValue":10,"c5_nullCount":0,"c6_maxValue":"2020-10-10","c6_minValue":"2020-01-10","c6_nullCount":0,"c7_maxValue":"yA==","c7_minValue":"LA==","c7_nullCount":0,"c8_maxValue":9,"c8_minValue":9,"c8_nullCount":0,"valueCount":10}
{"c1_maxValue":959,"c1_minValue":74,"c1_num_nulls":0,"c2_maxValue":" 959sdc","c2_minValue":" 181sdc","c2_num_nulls":0,"c3_maxValue":980.213,"c3_minValue":38.740,"c3_num_nulls":0,"c4_maxValue":"2021-11-19T20:40:55.550-08:00","c4_minValue":"2021-11-19T20:40:55.507-08:00","c4_num_nulls":0,"c5_maxValue":97,"c5_minValue":9,"c5_num_nulls":0,"c6_maxValue":"2020-11-22","c6_minValue":"2020-01-23","c6_num_nulls":0,"c7_maxValue":"1Q==","c7_minValue":"Kw==","c7_num_nulls":0,"c8_maxValue":9,"c8_minValue":9,"c8_num_nulls":0} {"c1_maxValue":959,"c1_minValue":74,"c1_nullCount":0,"c2_maxValue":" 959sdc","c2_minValue":" 181sdc","c2_nullCount":0,"c3_maxValue":980.213,"c3_minValue":38.740,"c3_nullCount":0,"c4_maxValue":"2021-11-19T20:40:55.550-08:00","c4_minValue":"2021-11-19T20:40:55.507-08:00","c4_nullCount":0,"c5_maxValue":97,"c5_minValue":9,"c5_nullCount":0,"c6_maxValue":"2020-11-22","c6_minValue":"2020-01-23","c6_nullCount":0,"c7_maxValue":"1Q==","c7_minValue":"Kw==","c7_nullCount":0,"c8_maxValue":9,"c8_minValue":9,"c8_nullCount":0,"valueCount":13}

16
hudi-spark-datasource/hudi-spark/src/test/resources/index/zorder/updated-column-stats-index-table.json
View File

@@ -1,8 +1,8 @@
{"c1_maxValue":568,"c1_minValue":8,"c1_num_nulls":0,"c2_maxValue":" 8sdc","c2_minValue":" 111sdc","c2_num_nulls":0,"c3_maxValue":979.272,"c3_minValue":82.111,"c3_num_nulls":0,"c4_maxValue":"2021-11-18T23:34:44.193-08:00","c4_minValue":"2021-11-18T23:34:44.159-08:00","c4_num_nulls":0,"c5_maxValue":58,"c5_minValue":2,"c5_num_nulls":0,"c6_maxValue":"2020-11-08","c6_minValue":"2020-01-01","c6_num_nulls":0,"c7_maxValue":"9g==","c7_minValue":"Ag==","c7_num_nulls":0,"c8_maxValue":9,"c8_minValue":9,"c8_num_nulls":0} {"c1_maxValue":568,"c1_minValue":8,"c1_nullCount":0,"c2_maxValue":" 8sdc","c2_minValue":" 111sdc","c2_nullCount":0,"c3_maxValue":979.272,"c3_minValue":82.111,"c3_nullCount":0,"c4_maxValue":"2021-11-18T23:34:44.193-08:00","c4_minValue":"2021-11-18T23:34:44.159-08:00","c4_nullCount":0,"c5_maxValue":58,"c5_minValue":2,"c5_nullCount":0,"c6_maxValue":"2020-11-08","c6_minValue":"2020-01-01","c6_nullCount":0,"c7_maxValue":"9g==","c7_minValue":"Ag==","c7_nullCount":0,"c8_maxValue":9,"c8_minValue":9,"c8_nullCount":0,"valueCount":15}
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314
hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/hudi/TestDataSkippingUtils.scala
View File

@@ -36,21 +36,22 @@ import scala.collection.JavaConverters._
// NOTE: Only A, B columns are indexed // NOTE: Only A, B columns are indexed
case class IndexRow(fileName: String, case class IndexRow(fileName: String,
valueCount: Long = 1,
// Corresponding A column is LongType // Corresponding A column is LongType
A_minValue: Long = -1, A_minValue: Long = -1,
A_maxValue: Long = -1, A_maxValue: Long = -1,
A_num_nulls: Long = -1, A_nullCount: Long = -1,
// Corresponding B column is StringType // Corresponding B column is StringType
B_minValue: String = null, B_minValue: String = null,
B_maxValue: String = null, B_maxValue: String = null,
B_num_nulls: Long = -1, B_nullCount: Long = -1,
// Corresponding B column is TimestampType // Corresponding B column is TimestampType
C_minValue: Timestamp = null, C_minValue: Timestamp = null,
C_maxValue: Timestamp = null, C_maxValue: Timestamp = null,
C_num_nulls: Long = -1) { C_nullCount: Long = -1) {
def toRow: Row = Row(productIterator.toSeq: _*) def toRow: Row = Row(productIterator.toSeq: _*)
} }
@@ -132,28 +133,28 @@ object TestDataSkippingUtils {
arguments( arguments(
col("B").startsWith("abc").expr, col("B").startsWith("abc").expr,
Seq( Seq(
IndexRow("file_1", 0, 0, 0, "aba", "adf", 1), // may contain strings starting w/ "abc" IndexRow("file_1", valueCount = 1, B_minValue = "aba", B_maxValue = "adf", B_nullCount = 1), // may contain strings starting w/ "abc"
IndexRow("file_2", 0, 0, 0, "adf", "azy", 0), IndexRow("file_2", valueCount = 1, B_minValue = "adf", B_maxValue = "azy", B_nullCount = 0),
IndexRow("file_3", 0, 0, 0, "aaa", "aba", 0) IndexRow("file_3", valueCount = 1, B_minValue = "aaa", B_maxValue = "aba", B_nullCount = 0)
), ),
Seq("file_1")), Seq("file_1")),
arguments( arguments(
Not(col("B").startsWith("abc").expr), Not(col("B").startsWith("abc").expr),
Seq( Seq(
IndexRow("file_1", 0, 0, 0, "aba", "adf", 1), // may contain strings starting w/ "abc" IndexRow("file_1", valueCount = 1, B_minValue = "aba", B_maxValue = "adf", B_nullCount = 1), // may contain strings starting w/ "abc"
IndexRow("file_2", 0, 0, 0, "adf", "azy", 0), IndexRow("file_2", valueCount = 1, B_minValue = "adf", B_maxValue = "azy", B_nullCount = 0),
IndexRow("file_3", 0, 0, 0, "aaa", "aba", 0), IndexRow("file_3", valueCount = 1, B_minValue = "aaa", B_maxValue = "aba", B_nullCount = 0),
IndexRow("file_4", 0, 0, 0, "abc123", "abc345", 0) // all strings start w/ "abc" IndexRow("file_4", valueCount = 1, B_minValue = "abc123", B_maxValue = "abc345", B_nullCount = 0) // all strings start w/ "abc"
), ),
Seq("file_1", "file_2", "file_3")), Seq("file_1", "file_2", "file_3")),
arguments( arguments(
// Composite expression // Composite expression
Not(lower(col("B")).startsWith("abc").expr), Not(lower(col("B")).startsWith("abc").expr),
Seq( Seq(
IndexRow("file_1", 0, 0, 0, "ABA", "ADF", 1), // may contain strings starting w/ "ABC" (after upper) IndexRow("file_1", valueCount = 1, B_minValue = "ABA", B_maxValue = "ADF", B_nullCount = 1), // may contain strings starting w/ "ABC" (after upper)
IndexRow("file_2", 0, 0, 0, "ADF", "AZY", 0), IndexRow("file_2", valueCount = 1, B_minValue = "ADF", B_maxValue = "AZY", B_nullCount = 0),
IndexRow("file_3", 0, 0, 0, "AAA", "ABA", 0), IndexRow("file_3", valueCount = 1, B_minValue = "AAA", B_maxValue = "ABA", B_nullCount = 0),
IndexRow("file_4", 0, 0, 0, "ABC123", "ABC345", 0) // all strings start w/ "ABC" (after upper) IndexRow("file_4", valueCount = 1, B_minValue = "ABC123", B_maxValue = "ABC345", B_nullCount = 0) // all strings start w/ "ABC" (after upper)
), ),
Seq("file_1", "file_2", "file_3")) Seq("file_1", "file_2", "file_3"))
) )
@@ -166,144 +167,151 @@ object TestDataSkippingUtils {
arguments( arguments(
"A = 0", "A = 0",
Seq( Seq(
IndexRow("file_1", 1, 2, 0), IndexRow("file_1", valueCount = 1, 1, 2, 0),
IndexRow("file_2", -1, 1, 0) IndexRow("file_2", valueCount = 1, -1, 1, 0)
), ),
Seq("file_2")), Seq("file_2")),
arguments( arguments(
"0 = A", "0 = A",
Seq( Seq(
IndexRow("file_1", 1, 2, 0), IndexRow("file_1", valueCount = 1, 1, 2, 0),
IndexRow("file_2", -1, 1, 0) IndexRow("file_2", valueCount = 1, -1, 1, 0)
), ),
Seq("file_2")), Seq("file_2")),
arguments( arguments(
"A != 0", "A != 0",
Seq( Seq(
IndexRow("file_1", 1, 2, 0), IndexRow("file_1", valueCount = 1, 1, 2, 0),
IndexRow("file_2", -1, 1, 0), IndexRow("file_2", valueCount = 1, -1, 1, 0),
IndexRow("file_3", 0, 0, 0) // Contains only 0s IndexRow("file_3", valueCount = 1, 0, 0, 0) // Contains only 0s
), ),
Seq("file_1", "file_2")), Seq("file_1", "file_2")),
arguments( arguments(
"0 != A", "0 != A",
Seq( Seq(
IndexRow("file_1", 1, 2, 0), IndexRow("file_1", valueCount = 1, 1, 2, 0),
IndexRow("file_2", -1, 1, 0), IndexRow("file_2", valueCount = 1, -1, 1, 0),
IndexRow("file_3", 0, 0, 0) // Contains only 0s IndexRow("file_3", valueCount = 1, 0, 0, 0) // Contains only 0s
), ),
Seq("file_1", "file_2")), Seq("file_1", "file_2")),
arguments( arguments(
"A < 0", "A < 0",
Seq( Seq(
IndexRow("file_1", 1, 2, 0), IndexRow("file_1", valueCount = 1, 1, 2, 0),
IndexRow("file_2", -1, 1, 0), IndexRow("file_2", valueCount = 1, -1, 1, 0),
IndexRow("file_3", -2, -1, 0) IndexRow("file_3", valueCount = 1, -2, -1, 0)
), ),
Seq("file_2", "file_3")), Seq("file_2", "file_3")),
arguments( arguments(
"0 > A", "0 > A",
Seq( Seq(
IndexRow("file_1", 1, 2, 0), IndexRow("file_1", valueCount = 1, 1, 2, 0),
IndexRow("file_2", -1, 1, 0), IndexRow("file_2", valueCount = 1, -1, 1, 0),
IndexRow("file_3", -2, -1, 0) IndexRow("file_3", valueCount = 1, -2, -1, 0)
), ),
Seq("file_2", "file_3")), Seq("file_2", "file_3")),
arguments( arguments(
"A > 0", "A > 0",
Seq( Seq(
IndexRow("file_1", 1, 2, 0), IndexRow("file_1", valueCount = 1, 1, 2, 0),
IndexRow("file_2", -1, 1, 0), IndexRow("file_2", valueCount = 1, -1, 1, 0),
IndexRow("file_3", -2, -1, 0) IndexRow("file_3", valueCount = 1, -2, -1, 0)
), ),
Seq("file_1", "file_2")), Seq("file_1", "file_2")),
arguments( arguments(
"0 < A", "0 < A",
Seq( Seq(
IndexRow("file_1", 1, 2, 0), IndexRow("file_1", valueCount = 1, 1, 2, 0),
IndexRow("file_2", -1, 1, 0), IndexRow("file_2", valueCount = 1, -1, 1, 0),
IndexRow("file_3", -2, -1, 0) IndexRow("file_3", valueCount = 1, -2, -1, 0)
), ),
Seq("file_1", "file_2")), Seq("file_1", "file_2")),
arguments( arguments(
"A <= -1", "A <= -1",
Seq( Seq(
IndexRow("file_1", 1, 2, 0), IndexRow("file_1", valueCount = 1, 1, 2, 0),
IndexRow("file_2", -1, 1, 0), IndexRow("file_2", valueCount = 1, -1, 1, 0),
IndexRow("file_3", -2, -1, 0) IndexRow("file_3", valueCount = 1, -2, -1, 0)
), ),
Seq("file_2", "file_3")), Seq("file_2", "file_3")),
arguments( arguments(
"-1 >= A", "-1 >= A",
Seq( Seq(
IndexRow("file_1", 1, 2, 0), IndexRow("file_1", valueCount = 1, 1, 2, 0),
IndexRow("file_2", -1, 1, 0), IndexRow("file_2", valueCount = 1, -1, 1, 0),
IndexRow("file_3", -2, -1, 0) IndexRow("file_3", valueCount = 1, -2, -1, 0)
), ),
Seq("file_2", "file_3")), Seq("file_2", "file_3")),
arguments( arguments(
"A >= 1", "A >= 1",
Seq( Seq(
IndexRow("file_1", 1, 2, 0), IndexRow("file_1", valueCount = 1, 1, 2, 0),
IndexRow("file_2", -1, 1, 0), IndexRow("file_2", valueCount = 1, -1, 1, 0),
IndexRow("file_3", -2, -1, 0) IndexRow("file_3", valueCount = 1, -2, -1, 0)
), ),
Seq("file_1", "file_2")), Seq("file_1", "file_2")),
arguments( arguments(
"1 <= A", "1 <= A",
Seq( Seq(
IndexRow("file_1", 1, 2, 0), IndexRow("file_1", valueCount = 1, 1, 2, 0),
IndexRow("file_2", -1, 1, 0), IndexRow("file_2", valueCount = 1, -1, 1, 0),
IndexRow("file_3", -2, -1, 0) IndexRow("file_3", valueCount = 1, -2, -1, 0)
), ),
Seq("file_1", "file_2")), Seq("file_1", "file_2")),
arguments( arguments(
"A is null", "A is null",
Seq( Seq(
IndexRow("file_1", 1, 2, 0), IndexRow("file_1", valueCount = 1, 1, 2, 0),
IndexRow("file_2", -1, 1, 1) IndexRow("file_2", valueCount = 1, -1, 1, 1)
), ),
Seq("file_2")), Seq("file_2")),
arguments( arguments(
"A is not null", "A is not null",
Seq( Seq(
IndexRow("file_1", 1, 2, 0), IndexRow("file_1", valueCount = 1, 1, 2, 0),
IndexRow("file_2", -1, 1, 1) IndexRow("file_2", valueCount = 2, -1, 1, 1) // might still contain non-null values (if nullCount < valueCount)
),
Seq("file_1", "file_2")),
arguments(
"A is not null",
Seq(
IndexRow("file_1", valueCount = 1, 1, 2, 0),
IndexRow("file_2", valueCount = 1, -1, 1, 1) // might NOT contain non-null values (nullCount == valueCount)
), ),
Seq("file_1")), Seq("file_1")),
arguments( arguments(
"A in (0, 1)", "A in (0, 1)",
Seq( Seq(
IndexRow("file_1", 1, 2, 0), IndexRow("file_1", valueCount = 1, 1, 2, 0),
IndexRow("file_2", -1, 1, 0), IndexRow("file_2", valueCount = 1, -1, 1, 0),
IndexRow("file_3", -2, -1, 0) IndexRow("file_3", valueCount = 1, -2, -1, 0)
), ),
Seq("file_1", "file_2")), Seq("file_1", "file_2")),
arguments( arguments(
"A not in (0, 1)", "A not in (0, 1)",
Seq( Seq(
IndexRow("file_1", 1, 2, 0), IndexRow("file_1", valueCount = 1, 1, 2, 0),
IndexRow("file_2", -1, 1, 0), IndexRow("file_2", valueCount = 1, -1, 1, 0),
IndexRow("file_3", -2, -1, 0), IndexRow("file_3", valueCount = 1, -2, -1, 0),
IndexRow("file_4", 0, 0, 0), // only contains 0 IndexRow("file_4", valueCount = 1, 0, 0, 0), // only contains 0
IndexRow("file_5", 1, 1, 0) // only contains 1 IndexRow("file_5", valueCount = 1, 1, 1, 0) // only contains 1
), ),
Seq("file_1", "file_2", "file_3")), Seq("file_1", "file_2", "file_3")),
arguments( arguments(
// Value expression containing expression, which isn't a literal // Value expression containing expression, which isn't a literal
"A = int('0')", "A = int('0')",
Seq( Seq(
IndexRow("file_1", 1, 2, 0), IndexRow("file_1", valueCount = 1, 1, 2, 0),
IndexRow("file_2", -1, 1, 0) IndexRow("file_2", valueCount = 1, -1, 1, 0)
), ),
Seq("file_2")), Seq("file_2")),
arguments( arguments(
// Value expression containing reference to the other attribute (column), fallback // Value expression containing reference to the other attribute (column), fallback
"A = D", "A = D",
Seq( Seq(
IndexRow("file_1", 1, 2, 0), IndexRow("file_1", valueCount = 1, 1, 2, 0),
IndexRow("file_2", -1, 1, 0), IndexRow("file_2", valueCount = 1, -1, 1, 0),
IndexRow("file_3", -2, -1, 0) IndexRow("file_3", valueCount = 1, -2, -1, 0)
), ),
Seq("file_1", "file_2", "file_3")) Seq("file_1", "file_2", "file_3"))
) )
@@ -315,22 +323,22 @@ object TestDataSkippingUtils {
// Filter out all rows that contain either A = 0 OR A = 1 // Filter out all rows that contain either A = 0 OR A = 1
"A != 0 AND A != 1", "A != 0 AND A != 1",
Seq( Seq(
IndexRow("file_1", 1, 2, 0), IndexRow("file_1", valueCount = 1, 1, 2, 0),
IndexRow("file_2", -1, 1, 0), IndexRow("file_2", valueCount = 1, -1, 1, 0),
IndexRow("file_3", -2, -1, 0), IndexRow("file_3", valueCount = 1, -2, -1, 0),
IndexRow("file_4", 0, 0, 0), // only contains 0 IndexRow("file_4", valueCount = 1, 0, 0, 0), // only contains 0
IndexRow("file_5", 1, 1, 0) // only contains 1 IndexRow("file_5", valueCount = 1, 1, 1, 0) // only contains 1
), ),
Seq("file_1", "file_2", "file_3")), Seq("file_1", "file_2", "file_3")),
arguments( arguments(
// This is an equivalent to the above expression // This is an equivalent to the above expression
"NOT(A = 0 OR A = 1)", "NOT(A = 0 OR A = 1)",
Seq( Seq(
IndexRow("file_1", 1, 2, 0), IndexRow("file_1", valueCount = 1, 1, 2, 0),
IndexRow("file_2", -1, 1, 0), IndexRow("file_2", valueCount = 1, -1, 1, 0),
IndexRow("file_3", -2, -1, 0), IndexRow("file_3", valueCount = 1, -2, -1, 0),
IndexRow("file_4", 0, 0, 0), // only contains 0 IndexRow("file_4", valueCount = 1, 0, 0, 0), // only contains 0
IndexRow("file_5", 1, 1, 0) // only contains 1 IndexRow("file_5", valueCount = 1, 1, 1, 0) // only contains 1
), ),
Seq("file_1", "file_2", "file_3")), Seq("file_1", "file_2", "file_3")),
@@ -338,22 +346,22 @@ object TestDataSkippingUtils {
// Filter out all rows that contain A = 0 AND B = 'abc' // Filter out all rows that contain A = 0 AND B = 'abc'
"A != 0 OR B != 'abc'", "A != 0 OR B != 'abc'",
Seq( Seq(
IndexRow("file_1", 1, 2, 0), IndexRow("file_1", valueCount = 1, A_minValue = 1, A_maxValue = 2, A_nullCount = 0),
IndexRow("file_2", -1, 1, 0), IndexRow("file_2", valueCount = 1, A_minValue = -1, A_maxValue = 1, A_nullCount = 0),
IndexRow("file_3", -2, -1, 0), IndexRow("file_3", valueCount = 1, A_minValue = -2, A_maxValue = -1, A_nullCount = 0),
IndexRow("file_4", 0, 0, 0, "abc", "abc", 0), // only contains A = 0, B = 'abc' IndexRow("file_4", valueCount = 1, A_minValue = 0, A_maxValue = 0, A_nullCount = 0, B_minValue = "abc", B_maxValue = "abc", B_nullCount = 0), // only contains A = 0, B = 'abc'
IndexRow("file_5", 0, 0, 0, "abc", "abc", 0) // only contains A = 0, B = 'abc' IndexRow("file_5", valueCount = 1, A_minValue = 0, A_maxValue = 0, A_nullCount = 0, B_minValue = "abc", B_maxValue = "abc", B_nullCount = 0) // only contains A = 0, B = 'abc'
), ),
Seq("file_1", "file_2", "file_3")), Seq("file_1", "file_2", "file_3")),
arguments( arguments(
// This is an equivalent to the above expression // This is an equivalent to the above expression
"NOT(A = 0 AND B = 'abc')", "NOT(A = 0 AND B = 'abc')",
Seq( Seq(
IndexRow("file_1", 1, 2, 0), IndexRow("file_1", valueCount = 1, A_minValue = 1, A_maxValue = 2, A_nullCount = 0),
IndexRow("file_2", -1, 1, 0), IndexRow("file_2", valueCount = 1, A_minValue = -1, A_maxValue = 1, A_nullCount = 0),
IndexRow("file_3", -2, -1, 0), IndexRow("file_3", valueCount = 1, A_minValue = -2, A_maxValue = -1, A_nullCount = 0),
IndexRow("file_4", 0, 0, 0, "abc", "abc", 0), // only contains A = 0, B = 'abc' IndexRow("file_4", valueCount = 1, A_minValue = 0, A_maxValue = 0, A_nullCount = 0, B_minValue = "abc", B_maxValue = "abc", B_nullCount = 0), // only contains A = 0, B = 'abc'
IndexRow("file_5", 0, 0, 0, "abc", "abc", 0) // only contains A = 0, B = 'abc' IndexRow("file_5", valueCount = 1, A_minValue = 0, A_maxValue = 0, A_nullCount = 0, B_minValue = "abc", B_maxValue = "abc", B_nullCount = 0) // only contains A = 0, B = 'abc'
), ),
Seq("file_1", "file_2", "file_3")), Seq("file_1", "file_2", "file_3")),
@@ -361,10 +369,10 @@ object TestDataSkippingUtils {
// Queries contains expression involving non-indexed column D // Queries contains expression involving non-indexed column D
"A = 0 AND B = 'abc' AND D IS NULL", "A = 0 AND B = 'abc' AND D IS NULL",
Seq( Seq(
IndexRow("file_1", 1, 2, 0), IndexRow("file_1", valueCount = 1, A_minValue = 1, A_maxValue = 2, A_nullCount = 0),
IndexRow("file_2", -1, 1, 0), IndexRow("file_2", valueCount = 1, A_minValue = -1, A_maxValue = 1, A_nullCount = 0),
IndexRow("file_3", -2, -1, 0), IndexRow("file_3", valueCount = 1, A_minValue = -2, A_maxValue = -1, A_nullCount = 0),
IndexRow("file_4", 0, 0, 0, "aaa", "xyz", 0) // might contain A = 0 AND B = 'abc' IndexRow("file_4", valueCount = 1, A_minValue = 0, A_maxValue = 0, A_nullCount = 0, B_minValue = "aaa", B_maxValue = "xyz", B_nullCount = 0) // might contain A = 0 AND B = 'abc'
), ),
Seq("file_4")), Seq("file_4")),
@@ -372,10 +380,10 @@ object TestDataSkippingUtils {
// Queries contains expression involving non-indexed column D // Queries contains expression involving non-indexed column D
"A = 0 OR B = 'abc' OR D IS NULL", "A = 0 OR B = 'abc' OR D IS NULL",
Seq( Seq(
IndexRow("file_1", 1, 2, 0), IndexRow("file_1", valueCount = 1, A_minValue = 1, A_maxValue = 2, A_nullCount = 0),
IndexRow("file_2", -1, 1, 0), IndexRow("file_2", valueCount = 1, A_minValue = -1, A_maxValue = 1, A_nullCount = 0),
IndexRow("file_3", -2, -1, 0), IndexRow("file_3", valueCount = 1, A_minValue = -2, A_maxValue = -1, A_nullCount = 0),
IndexRow("file_4", 0, 0, 0, "aaa", "xyz", 0) // might contain B = 'abc' IndexRow("file_4", valueCount = 1, B_minValue = "aaa", B_maxValue = "xyz", B_nullCount = 0) // might contain B = 'abc'
), ),
Seq("file_1", "file_2", "file_3", "file_4")) Seq("file_1", "file_2", "file_3", "file_4"))
) )
@@ -387,197 +395,197 @@ object TestDataSkippingUtils {
arguments( arguments(
"date_format(C, 'MM/dd/yyyy') = '03/07/2022'", "date_format(C, 'MM/dd/yyyy') = '03/07/2022'",
Seq( Seq(
IndexRow("file_1", IndexRow("file_1", valueCount = 1,
C_minValue = new Timestamp(1646711448000L), // 03/08/2022 C_minValue = new Timestamp(1646711448000L), // 03/08/2022
C_maxValue = new Timestamp(1646797848000L), // 03/09/2022 C_maxValue = new Timestamp(1646797848000L), // 03/09/2022
C_num_nulls = 0), C_nullCount = 0),
IndexRow("file_2", IndexRow("file_2", valueCount = 1,
C_minValue = new Timestamp(1646625048000L), // 03/07/2022 C_minValue = new Timestamp(1646625048000L), // 03/07/2022
C_maxValue = new Timestamp(1646711448000L), // 03/08/2022 C_maxValue = new Timestamp(1646711448000L), // 03/08/2022
C_num_nulls = 0) C_nullCount = 0)
), ),
Seq("file_2")), Seq("file_2")),
arguments( arguments(
"'03/07/2022' = date_format(C, 'MM/dd/yyyy')", "'03/07/2022' = date_format(C, 'MM/dd/yyyy')",
Seq( Seq(
IndexRow("file_1", IndexRow("file_1", valueCount = 1,
C_minValue = new Timestamp(1646711448000L), // 03/08/2022 C_minValue = new Timestamp(1646711448000L), // 03/08/2022
C_maxValue = new Timestamp(1646797848000L), // 03/09/2022 C_maxValue = new Timestamp(1646797848000L), // 03/09/2022
C_num_nulls = 0), C_nullCount = 0),
IndexRow("file_2", IndexRow("file_2", valueCount = 1,
C_minValue = new Timestamp(1646625048000L), // 03/07/2022 C_minValue = new Timestamp(1646625048000L), // 03/07/2022
C_maxValue = new Timestamp(1646711448000L), // 03/08/2022 C_maxValue = new Timestamp(1646711448000L), // 03/08/2022
C_num_nulls = 0) C_nullCount = 0)
), ),
Seq("file_2")), Seq("file_2")),
arguments( arguments(
"'03/07/2022' != date_format(C, 'MM/dd/yyyy')", "'03/07/2022' != date_format(C, 'MM/dd/yyyy')",
Seq( Seq(
IndexRow("file_1", IndexRow("file_1", valueCount = 1,
C_minValue = new Timestamp(1646711448000L), // 03/08/2022 C_minValue = new Timestamp(1646711448000L), // 03/08/2022
C_maxValue = new Timestamp(1646797848000L), // 03/09/2022 C_maxValue = new Timestamp(1646797848000L), // 03/09/2022
C_num_nulls = 0), C_nullCount = 0),
IndexRow("file_2", IndexRow("file_2", valueCount = 1,
C_minValue = new Timestamp(1646625048000L), // 03/07/2022 C_minValue = new Timestamp(1646625048000L), // 03/07/2022
C_maxValue = new Timestamp(1646625048000L), // 03/07/2022 C_maxValue = new Timestamp(1646625048000L), // 03/07/2022
C_num_nulls = 0) C_nullCount = 0)
), ),
Seq("file_1")), Seq("file_1")),
arguments( arguments(
"date_format(C, 'MM/dd/yyyy') != '03/07/2022'", "date_format(C, 'MM/dd/yyyy') != '03/07/2022'",
Seq( Seq(
IndexRow("file_1", IndexRow("file_1", valueCount = 1,
C_minValue = new Timestamp(1646711448000L), // 03/08/2022 C_minValue = new Timestamp(1646711448000L), // 03/08/2022
C_maxValue = new Timestamp(1646797848000L), // 03/09/2022 C_maxValue = new Timestamp(1646797848000L), // 03/09/2022
C_num_nulls = 0), C_nullCount = 0),
IndexRow("file_2", IndexRow("file_2", valueCount = 1,
C_minValue = new Timestamp(1646625048000L), // 03/07/2022 C_minValue = new Timestamp(1646625048000L), // 03/07/2022
C_maxValue = new Timestamp(1646625048000L), // 03/07/2022 C_maxValue = new Timestamp(1646625048000L), // 03/07/2022
C_num_nulls = 0) C_nullCount = 0)
), ),
Seq("file_1")), Seq("file_1")),
arguments( arguments(
"date_format(C, 'MM/dd/yyyy') < '03/08/2022'", "date_format(C, 'MM/dd/yyyy') < '03/08/2022'",
Seq( Seq(
IndexRow("file_1", IndexRow("file_1", valueCount = 1,
C_minValue = new Timestamp(1646711448000L), // 03/08/2022 C_minValue = new Timestamp(1646711448000L), // 03/08/2022
C_maxValue = new Timestamp(1646797848000L), // 03/09/2022 C_maxValue = new Timestamp(1646797848000L), // 03/09/2022
C_num_nulls = 0), C_nullCount = 0),
IndexRow("file_2", IndexRow("file_2", valueCount = 1,
C_minValue = new Timestamp(1646625048000L), // 03/07/2022 C_minValue = new Timestamp(1646625048000L), // 03/07/2022
C_maxValue = new Timestamp(1646711448000L), // 03/08/2022 C_maxValue = new Timestamp(1646711448000L), // 03/08/2022
C_num_nulls = 0) C_nullCount = 0)
), ),
Seq("file_2")), Seq("file_2")),
arguments( arguments(
"'03/08/2022' > date_format(C, 'MM/dd/yyyy')", "'03/08/2022' > date_format(C, 'MM/dd/yyyy')",
Seq( Seq(
IndexRow("file_1", IndexRow("file_1", valueCount = 1,
C_minValue = new Timestamp(1646711448000L), // 03/08/2022 C_minValue = new Timestamp(1646711448000L), // 03/08/2022
C_maxValue = new Timestamp(1646797848000L), // 03/09/2022 C_maxValue = new Timestamp(1646797848000L), // 03/09/2022
C_num_nulls = 0), C_nullCount = 0),
IndexRow("file_2", IndexRow("file_2", valueCount = 1,
C_minValue = new Timestamp(1646625048000L), // 03/07/2022 C_minValue = new Timestamp(1646625048000L), // 03/07/2022
C_maxValue = new Timestamp(1646711448000L), // 03/08/2022 C_maxValue = new Timestamp(1646711448000L), // 03/08/2022
C_num_nulls = 0) C_nullCount = 0)
), ),
Seq("file_2")), Seq("file_2")),
arguments( arguments(
"'03/08/2022' < date_format(C, 'MM/dd/yyyy')", "'03/08/2022' < date_format(C, 'MM/dd/yyyy')",
Seq( Seq(
IndexRow("file_1", IndexRow("file_1", valueCount = 1,
C_minValue = new Timestamp(1646711448000L), // 03/08/2022 C_minValue = new Timestamp(1646711448000L), // 03/08/2022
C_maxValue = new Timestamp(1646797848000L), // 03/09/2022 C_maxValue = new Timestamp(1646797848000L), // 03/09/2022
C_num_nulls = 0), C_nullCount = 0),
IndexRow("file_2", IndexRow("file_2", valueCount = 1,
C_minValue = new Timestamp(1646625048000L), // 03/07/2022 C_minValue = new Timestamp(1646625048000L), // 03/07/2022
C_maxValue = new Timestamp(1646711448000L), // 03/08/2022 C_maxValue = new Timestamp(1646711448000L), // 03/08/2022
C_num_nulls = 0) C_nullCount = 0)
), ),
Seq("file_1")), Seq("file_1")),
arguments( arguments(
"date_format(C, 'MM/dd/yyyy') > '03/08/2022'", "date_format(C, 'MM/dd/yyyy') > '03/08/2022'",
Seq( Seq(
IndexRow("file_1", IndexRow("file_1", valueCount = 1,
C_minValue = new Timestamp(1646711448000L), // 03/08/2022 C_minValue = new Timestamp(1646711448000L), // 03/08/2022
C_maxValue = new Timestamp(1646797848000L), // 03/09/2022 C_maxValue = new Timestamp(1646797848000L), // 03/09/2022
C_num_nulls = 0), C_nullCount = 0),
IndexRow("file_2", IndexRow("file_2", valueCount = 1,
C_minValue = new Timestamp(1646625048000L), // 03/07/2022 C_minValue = new Timestamp(1646625048000L), // 03/07/2022
C_maxValue = new Timestamp(1646711448000L), // 03/08/2022 C_maxValue = new Timestamp(1646711448000L), // 03/08/2022
C_num_nulls = 0) C_nullCount = 0)
), ),
Seq("file_1")), Seq("file_1")),
arguments( arguments(
"date_format(C, 'MM/dd/yyyy') <= '03/07/2022'", "date_format(C, 'MM/dd/yyyy') <= '03/07/2022'",
Seq( Seq(
IndexRow("file_1", IndexRow("file_1", valueCount = 1,
C_minValue = new Timestamp(1646711448000L), // 03/08/2022 C_minValue = new Timestamp(1646711448000L), // 03/08/2022
C_maxValue = new Timestamp(1646797848000L), // 03/09/2022 C_maxValue = new Timestamp(1646797848000L), // 03/09/2022
C_num_nulls = 0), C_nullCount = 0),
IndexRow("file_2", IndexRow("file_2", valueCount = 1,
C_minValue = new Timestamp(1646625048000L), // 03/07/2022 C_minValue = new Timestamp(1646625048000L), // 03/07/2022
C_maxValue = new Timestamp(1646711448000L), // 03/08/2022 C_maxValue = new Timestamp(1646711448000L), // 03/08/2022
C_num_nulls = 0) C_nullCount = 0)
), ),
Seq("file_2")), Seq("file_2")),
arguments( arguments(
"'03/07/2022' >= date_format(C, 'MM/dd/yyyy')", "'03/07/2022' >= date_format(C, 'MM/dd/yyyy')",
Seq( Seq(
IndexRow("file_1", IndexRow("file_1", valueCount = 1,
C_minValue = new Timestamp(1646711448000L), // 03/08/2022 C_minValue = new Timestamp(1646711448000L), // 03/08/2022
C_maxValue = new Timestamp(1646797848000L), // 03/09/2022 C_maxValue = new Timestamp(1646797848000L), // 03/09/2022
C_num_nulls = 0), C_nullCount = 0),
IndexRow("file_2", IndexRow("file_2", valueCount = 1,
C_minValue = new Timestamp(1646625048000L), // 03/07/2022 C_minValue = new Timestamp(1646625048000L), // 03/07/2022
C_maxValue = new Timestamp(1646711448000L), // 03/08/2022 C_maxValue = new Timestamp(1646711448000L), // 03/08/2022
C_num_nulls = 0) C_nullCount = 0)
), ),
Seq("file_2")), Seq("file_2")),
arguments( arguments(
"'03/09/2022' <= date_format(C, 'MM/dd/yyyy')", "'03/09/2022' <= date_format(C, 'MM/dd/yyyy')",
Seq( Seq(
IndexRow("file_1", IndexRow("file_1", valueCount = 1,
C_minValue = new Timestamp(1646711448000L), // 03/08/2022 C_minValue = new Timestamp(1646711448000L), // 03/08/2022
C_maxValue = new Timestamp(1646797848000L), // 03/09/2022 C_maxValue = new Timestamp(1646797848000L), // 03/09/2022
C_num_nulls = 0), C_nullCount = 0),
IndexRow("file_2", IndexRow("file_2", valueCount = 1,
C_minValue = new Timestamp(1646625048000L), // 03/07/2022 C_minValue = new Timestamp(1646625048000L), // 03/07/2022
C_maxValue = new Timestamp(1646711448000L), // 03/08/2022 C_maxValue = new Timestamp(1646711448000L), // 03/08/2022
C_num_nulls = 0) C_nullCount = 0)
), ),
Seq("file_1")), Seq("file_1")),
arguments( arguments(
"date_format(C, 'MM/dd/yyyy') >= '03/09/2022'", "date_format(C, 'MM/dd/yyyy') >= '03/09/2022'",
Seq( Seq(
IndexRow("file_1", IndexRow("file_1", valueCount = 1,
C_minValue = new Timestamp(1646711448000L), // 03/08/2022 C_minValue = new Timestamp(1646711448000L), // 03/08/2022
C_maxValue = new Timestamp(1646797848000L), // 03/09/2022 C_maxValue = new Timestamp(1646797848000L), // 03/09/2022
C_num_nulls = 0), C_nullCount = 0),
IndexRow("file_2", IndexRow("file_2", valueCount = 1,
C_minValue = new Timestamp(1646625048000L), // 03/07/2022 C_minValue = new Timestamp(1646625048000L), // 03/07/2022
C_maxValue = new Timestamp(1646711448000L), // 03/08/2022 C_maxValue = new Timestamp(1646711448000L), // 03/08/2022
C_num_nulls = 0) C_nullCount = 0)
), ),
Seq("file_1")), Seq("file_1")),
arguments( arguments(
"date_format(C, 'MM/dd/yyyy') IN ('03/09/2022')", "date_format(C, 'MM/dd/yyyy') IN ('03/09/2022')",
Seq( Seq(
IndexRow("file_1", IndexRow("file_1", valueCount = 1,
C_minValue = new Timestamp(1646711448000L), // 03/08/2022 C_minValue = new Timestamp(1646711448000L), // 03/08/2022
C_maxValue = new Timestamp(1646797848000L), // 03/09/2022 C_maxValue = new Timestamp(1646797848000L), // 03/09/2022
C_num_nulls = 0), C_nullCount = 0),
IndexRow("file_2", IndexRow("file_2", valueCount = 1,
C_minValue = new Timestamp(1646625048000L), // 03/07/2022 C_minValue = new Timestamp(1646625048000L), // 03/07/2022
C_maxValue = new Timestamp(1646711448000L), // 03/08/2022 C_maxValue = new Timestamp(1646711448000L), // 03/08/2022
C_num_nulls = 0) C_nullCount = 0)
), ),
Seq("file_1")), Seq("file_1")),
arguments( arguments(
"date_format(C, 'MM/dd/yyyy') NOT IN ('03/07/2022')", "date_format(C, 'MM/dd/yyyy') NOT IN ('03/07/2022')",
Seq( Seq(
IndexRow("file_1", IndexRow("file_1", valueCount = 1,
C_minValue = new Timestamp(1646711448000L), // 03/08/2022 C_minValue = new Timestamp(1646711448000L), // 03/08/2022
C_maxValue = new Timestamp(1646797848000L), // 03/09/2022 C_maxValue = new Timestamp(1646797848000L), // 03/09/2022
C_num_nulls = 0), C_nullCount = 0),
IndexRow("file_2", IndexRow("file_2", valueCount = 1,
C_minValue = new Timestamp(1646625048000L), // 03/07/2022 C_minValue = new Timestamp(1646625048000L), // 03/07/2022
C_maxValue = new Timestamp(1646625048000L), // 03/07/2022 C_maxValue = new Timestamp(1646625048000L), // 03/07/2022
C_num_nulls = 0) C_nullCount = 0)
), ),
Seq("file_1")), Seq("file_1")),
arguments( arguments(
// Should be identical to the one above // Should be identical to the one above
"date_format(to_timestamp(B, 'yyyy-MM-dd'), 'MM/dd/yyyy') NOT IN ('03/06/2022')", "date_format(to_timestamp(B, 'yyyy-MM-dd'), 'MM/dd/yyyy') NOT IN ('03/06/2022')",
Seq( Seq(
IndexRow("file_1", IndexRow("file_1", valueCount = 1,
B_minValue = "2022-03-07", // 03/07/2022 B_minValue = "2022-03-07", // 03/07/2022
B_maxValue = "2022-03-08", // 03/08/2022 B_maxValue = "2022-03-08", // 03/08/2022
B_num_nulls = 0), B_nullCount = 0),
IndexRow("file_2", IndexRow("file_2", valueCount = 1,
B_minValue = "2022-03-06", // 03/06/2022 B_minValue = "2022-03-06", // 03/06/2022
B_maxValue = "2022-03-06", // 03/06/2022 B_maxValue = "2022-03-06", // 03/06/2022
B_num_nulls = 0) B_nullCount = 0)
), ),
Seq("file_1")) Seq("file_1"))

7
hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/hudi/functional/TestColumnStatsIndex.scala
View File

@@ -209,7 +209,7 @@ class TestColumnStatsIndex extends HoodieClientTestBase with ColumnStatsIndexSup
}) })
} }
private def buildColumnStatsTableManually(tablePath: String, zorderedCols: Seq[String], indexSchema: StructType) = { private def buildColumnStatsTableManually(tablePath: String, indexedCols: Seq[String], indexSchema: StructType) = {
val files = { val files = {
val it = fs.listFiles(new Path(tablePath), true) val it = fs.listFiles(new Path(tablePath), true)
var seq = Seq[LocatedFileStatus]() var seq = Seq[LocatedFileStatus]()
@@ -224,15 +224,16 @@ class TestColumnStatsIndex extends HoodieClientTestBase with ColumnStatsIndexSup
val df = spark.read.schema(sourceTableSchema).parquet(file.getPath.toString) val df = spark.read.schema(sourceTableSchema).parquet(file.getPath.toString)
val exprs: Seq[String] = val exprs: Seq[String] =
s"'${typedLit(file.getPath.getName)}' AS file" +: s"'${typedLit(file.getPath.getName)}' AS file" +:
s"sum(1) AS valueCount" +:
df.columns df.columns
.filter(col => zorderedCols.contains(col)) .filter(col => indexedCols.contains(col))
.flatMap(col => { .flatMap(col => {
val minColName = s"${col}_minValue" val minColName = s"${col}_minValue"
val maxColName = s"${col}_maxValue" val maxColName = s"${col}_maxValue"
Seq( Seq(
s"min($col) AS $minColName", s"min($col) AS $minColName",
s"max($col) AS $maxColName", s"max($col) AS $maxColName",
s"sum(cast(isnull($col) AS long)) AS ${col}_num_nulls" s"sum(cast(isnull($col) AS long)) AS ${col}_nullCount"
) )
}) })