1
0

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

- 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

View File

@@ -54,7 +54,8 @@ trait ColumnStatsIndexSupport extends SparkAdapterSupport {
HoodieMetadataPayload.COLUMN_STATS_FIELD_FILE_NAME,
HoodieMetadataPayload.COLUMN_STATS_FIELD_MIN_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 =
(targetColStatsIndexColumns :+ HoodieMetadataPayload.COLUMN_STATS_FIELD_COLUMN_NAME).map(colName =>
@@ -98,7 +99,7 @@ trait ColumnStatsIndexSupport extends SparkAdapterSupport {
*
* <pre>
* +---------------------------+------------+------------+-------------+
* | file | A_minValue | A_maxValue | A_num_nulls |
* | file | A_minValue | A_maxValue | A_nullCount |
* +---------------------------+------------+------------+-------------+
* | one_base_file.parquet | 1 | 10 | 0 |
* | 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 fileNameOrdinal = colStatsSchemaOrdinalsMap(HoodieMetadataPayload.COLUMN_STATS_FIELD_FILE_NAME)
val nullCountOrdinal = colStatsSchemaOrdinalsMap(HoodieMetadataPayload.COLUMN_STATS_FIELD_NULL_COUNT)
val valueCountOrdinal = colStatsSchemaOrdinalsMap(HoodieMetadataPayload.COLUMN_STATS_FIELD_VALUE_COUNT)
val transposedRDD = colStatsDF.rdd
.filter(row => sortedColumns.contains(row.getString(colNameOrdinal)))
@@ -155,11 +157,13 @@ trait ColumnStatsIndexSupport extends SparkAdapterSupport {
case (_, columnRows) =>
// Rows seq is always non-empty (otherwise it won't be grouped into)
val fileName = columnRows.head.get(fileNameOrdinal)
val valueCount = columnRows.head.get(valueCountOrdinal)
val coalescedRowValuesSeq = columnRows.toSeq
// NOTE: It's crucial to maintain appropriate ordering of the columns
// matching table layout
.sortBy(_.getString(colNameOrdinal))
.foldLeft(Seq[Any](fileName)) {
.foldLeft(Seq[Any](fileName, valueCount)) {
case (acc, columnRow) =>
acc ++ Seq(minValueOrdinal, maxValueOrdinal, nullCountOrdinal).map(ord => columnRow.get(ord))
}
@@ -223,11 +227,6 @@ trait ColumnStatsIndexSupport extends SparkAdapterSupport {
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$.toString
private val metadataRecordStructType: StructType = AvroConversionUtils.convertAvroSchemaToStructType(HoodieMetadataRecord.SCHEMA$)
@@ -235,28 +234,33 @@ object ColumnStatsIndexSupport {
* @VisibleForTesting
*/
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)
StructType(
targetFields.foldLeft(Seq(fileNameField)) {
targetFields.foldLeft(Seq(fileNameField, valueCountField)) {
case (acc, field) =>
acc ++ Seq(
composeColumnStatStructType(field.name, COLUMN_STATS_INDEX_MIN_VALUE_STAT_NAME, field.dataType),
composeColumnStatStructType(field.name, COLUMN_STATS_INDEX_MAX_VALUE_STAT_NAME, field.dataType),
composeColumnStatStructType(field.name, COLUMN_STATS_INDEX_NUM_NULLS_STAT_NAME, LongType))
composeColumnStatStructType(field.name, HoodieMetadataPayload.COLUMN_STATS_FIELD_MIN_VALUE, field.dataType),
composeColumnStatStructType(field.name, HoodieMetadataPayload.COLUMN_STATS_FIELD_MAX_VALUE, field.dataType),
composeColumnStatStructType(field.name, HoodieMetadataPayload.COLUMN_STATS_FIELD_NULL_COUNT, LongType))
}
)
}
@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 =
formatColName(colName, COLUMN_STATS_INDEX_MAX_VALUE_STAT_NAME)
formatColName(colName, HoodieMetadataPayload.COLUMN_STATS_FIELD_MAX_VALUE)
@inline def getNumNullsColumnNameFor(colName: String): String =
formatColName(colName, COLUMN_STATS_INDEX_NUM_NULLS_STAT_NAME)
@inline def getNullCountColumnNameFor(colName: String): String =
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
String.format("%s_%s", col, statName)

View File

@@ -26,12 +26,13 @@ import org.apache.hudi.common.util.StringUtils
import org.apache.hudi.exception.HoodieException
import org.apache.hudi.keygen.constant.KeyGeneratorOptions
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.sql.catalyst.InternalRow
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.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.types._
import org.apache.spark.sql.{Column, DataFrame, SparkSession}
@@ -211,7 +212,7 @@ case class HoodieFileIndex(spark: SparkSession,
withPersistence(transposedColStatsDF) {
val indexSchema = transposedColStatsDF.schema
val indexFilter =
queryFilters.map(DataSkippingUtils.translateIntoColumnStatsIndexFilterExpr(_, indexSchema))
queryFilters.map(translateIntoColumnStatsIndexFilterExpr(_, indexSchema))
.reduce(And)
val allIndexedFileNames =

View File

@@ -17,7 +17,7 @@
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.common.util.ValidationUtils.checkState
import org.apache.spark.internal.Logging
@@ -135,7 +135,7 @@ object DataSkippingUtils extends Logging {
}
// 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, _)) =>
getTargetIndexedColumnName(attrRef, indexSchema)
.map(colName => EqualTo(genColNumNullsExpr(colName), litNull))
@@ -205,16 +205,16 @@ object DataSkippingUtils extends Logging {
}
// 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) =>
getTargetIndexedColumnName(attribute, indexSchema)
.map(colName => GreaterThan(genColNumNullsExpr(colName), Literal(0)))
// 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) =>
getTargetIndexedColumnName(attribute, indexSchema)
.map(colName => EqualTo(genColNumNullsExpr(colName), Literal(0)))
.map(colName => LessThan(genColNumNullsExpr(colName), genColValueCountExpr))
// Filter "expr(colA) in (B1, 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(
getMinColumnNameFor(colName),
getMaxColumnNameFor(colName),
getNumNullsColumnNameFor(colName)
getNullCountColumnNameFor(colName)
)
.forall(stat => indexSchema.exists(_.name == stat))
}
@@ -325,19 +325,14 @@ object DataSkippingUtils extends Logging {
private object ColumnStatsExpressionUtils {
def genColMinValueExpr(colName: String): Expression =
col(getMinColumnNameFor(colName)).expr
def genColMaxValueExpr(colName: String): Expression =
col(getMaxColumnNameFor(colName)).expr
def genColNumNullsExpr(colName: String): Expression =
col(getNumNullsColumnNameFor(colName)).expr
@inline def genColMinValueExpr(colName: String): Expression = col(getMinColumnNameFor(colName)).expr
@inline def genColMaxValueExpr(colName: String): Expression = col(getMaxColumnNameFor(colName)).expr
@inline def genColNumNullsExpr(colName: String): Expression = col(getNullCountColumnNameFor(colName)).expr
@inline def genColValueCountExpr: Expression = col(getValueCountColumnNameFor).expr
def genColumnValuesEqualToExpression(colName: String,
@inline def genColumnValuesEqualToExpression(colName: String,
value: Expression,
targetExprBuilder: Function[Expression, Expression] = Predef.identity): Expression = {
// TODO clean up
checkState(isValueExpression(value))
val minValueExpr = targetExprBuilder.apply(genColMinValueExpr(colName))
val maxValueExpr = targetExprBuilder.apply(genColMaxValueExpr(colName))
// 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,
value: Expression,
targetExprBuilder: Function[Expression, Expression] = Predef.identity): Expression = {
// TODO clean up
checkState(isValueExpression(value))
val minValueExpr = targetExprBuilder.apply(genColMinValueExpr(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

View File

@@ -130,7 +130,7 @@ public class ColumnStatsIndexHelper {
*
* <pre>
* +---------------------------+------------+------------+-------------+
* | file | A_minValue | A_maxValue | A_num_nulls |
* | file | A_minValue | A_maxValue | A_nullCount |
* +---------------------------+------------+------------+-------------+
* | one_base_file.parquet | 1 | 10 | 0 |
* | another_base_file.parquet | -10 | 0 | 5 |

View File

@@ -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":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":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":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":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_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_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_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}

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":715,"c1_minValue":76,"c1_num_nulls":0,"c2_maxValue":" 76sdc","c2_minValue":" 224sdc","c2_num_nulls":0,"c3_maxValue":958.579,"c3_minValue":246.427,"c3_num_nulls":0,"c4_maxValue":"2021-11-18T23:34:44.199-08:00","c4_minValue":"2021-11-18T23:34:44.166-08:00","c4_num_nulls":0,"c5_maxValue":73,"c5_minValue":9,"c5_num_nulls":0,"c6_maxValue":"2020-11-21","c6_minValue":"2020-01-16","c6_num_nulls":0,"c7_maxValue":"+g==","c7_minValue":"LA==","c7_num_nulls":0,"c8_maxValue":9,"c8_minValue":9,"c8_num_nulls":0}
{"c1_maxValue":768,"c1_minValue":59,"c1_num_nulls":0,"c2_maxValue":" 768sdc","c2_minValue":" 118sdc","c2_num_nulls":0,"c3_maxValue":959.131,"c3_minValue":64.768,"c3_num_nulls":0,"c4_maxValue":"2021-11-18T23:34:44.201-08:00","c4_minValue":"2021-11-18T23:34:44.164-08:00","c4_num_nulls":0,"c5_maxValue":78,"c5_minValue":7,"c5_num_nulls":0,"c6_maxValue":"2020-11-20","c6_minValue":"2020-05-04","c6_num_nulls":0,"c7_maxValue":"zw==","c7_minValue":"AA==","c7_num_nulls":0,"c8_maxValue":9,"c8_minValue":9,"c8_num_nulls":0}
{"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":770,"c1_minValue":129,"c1_num_nulls":0,"c2_maxValue":" 770sdc","c2_minValue":" 129sdc","c2_num_nulls":0,"c3_maxValue":977.328,"c3_minValue":153.431,"c3_num_nulls":0,"c4_maxValue":"2021-11-18T23:34:44.201-08:00","c4_minValue":"2021-11-18T23:34:44.169-08:00","c4_num_nulls":0,"c5_maxValue":78,"c5_minValue":14,"c5_num_nulls":0,"c6_maxValue":"2020-10-21","c6_minValue":"2020-01-15","c6_num_nulls":0,"c7_maxValue":"rw==","c7_minValue":"Ag==","c7_num_nulls":0,"c8_maxValue":9,"c8_minValue":9,"c8_num_nulls":0}
{"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":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":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":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}
{"c1_maxValue":715,"c1_minValue":76,"c1_nullCount":0,"c2_maxValue":" 76sdc","c2_minValue":" 224sdc","c2_nullCount":0,"c3_maxValue":958.579,"c3_minValue":246.427,"c3_nullCount":0,"c4_maxValue":"2021-11-18T23:34:44.199-08:00","c4_minValue":"2021-11-18T23:34:44.166-08:00","c4_nullCount":0,"c5_maxValue":73,"c5_minValue":9,"c5_nullCount":0,"c6_maxValue":"2020-11-21","c6_minValue":"2020-01-16","c6_nullCount":0,"c7_maxValue":"+g==","c7_minValue":"LA==","c7_nullCount":0,"c8_maxValue":9,"c8_minValue":9,"c8_nullCount":0,"valueCount":12}
{"c1_maxValue":768,"c1_minValue":59,"c1_nullCount":0,"c2_maxValue":" 768sdc","c2_minValue":" 118sdc","c2_nullCount":0,"c3_maxValue":959.131,"c3_minValue":64.768,"c3_nullCount":0,"c4_maxValue":"2021-11-18T23:34:44.201-08:00","c4_minValue":"2021-11-18T23:34:44.164-08:00","c4_nullCount":0,"c5_maxValue":78,"c5_minValue":7,"c5_nullCount":0,"c6_maxValue":"2020-11-20","c6_minValue":"2020-05-04","c6_nullCount":0,"c7_maxValue":"zw==","c7_minValue":"AA==","c7_nullCount":0,"c8_maxValue":9,"c8_minValue":9,"c8_nullCount":0,"valueCount":7}
{"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":770,"c1_minValue":129,"c1_nullCount":0,"c2_maxValue":" 770sdc","c2_minValue":" 129sdc","c2_nullCount":0,"c3_maxValue":977.328,"c3_minValue":153.431,"c3_nullCount":0,"c4_maxValue":"2021-11-18T23:34:44.201-08:00","c4_minValue":"2021-11-18T23:34:44.169-08:00","c4_nullCount":0,"c5_maxValue":78,"c5_minValue":14,"c5_nullCount":0,"c6_maxValue":"2020-10-21","c6_minValue":"2020-01-15","c6_nullCount":0,"c7_maxValue":"rw==","c7_minValue":"Ag==","c7_nullCount":0,"c8_maxValue":9,"c8_minValue":9,"c8_nullCount":0,"valueCount":6}
{"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_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_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}

View File

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

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 it = fs.listFiles(new Path(tablePath), true)
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 exprs: Seq[String] =
s"'${typedLit(file.getPath.getName)}' AS file" +:
s"sum(1) AS valueCount" +:
df.columns
.filter(col => zorderedCols.contains(col))
.filter(col => indexedCols.contains(col))
.flatMap(col => {
val minColName = s"${col}_minValue"
val maxColName = s"${col}_maxValue"
Seq(
s"min($col) AS $minColName",
s"max($col) AS $maxColName",
s"sum(cast(isnull($col) AS long)) AS ${col}_num_nulls"
s"sum(cast(isnull($col) AS long)) AS ${col}_nullCount"
)
})