holdenk commented on a change in pull request #1421:
URL: https://github.com/apache/iceberg/pull/1421#discussion_r505809527
##########
File path: core/src/main/java/org/apache/iceberg/util/SnapshotUtil.java
##########
@@ -107,4 +112,47 @@ public static boolean ancestorOf(Table table, long
snapshotId, long ancestorSnap
return newFiles;
}
+
+ public static List<Snapshot> snapshotsWithin(Table table, long
fromSnapshotId, long toSnapshotId) {
+ List<Long> snapshotIds = SnapshotUtil.snapshotIdsBetween(table,
fromSnapshotId, toSnapshotId);
+ List<Snapshot> snapshots = Lists.newArrayList();
+ for (Long snapshotId : snapshotIds) {
+ Snapshot snapshot = table.snapshot(snapshotId);
+ // for now, incremental scan supports only appends
+ if (snapshot.operation().equals(DataOperations.APPEND)) {
+ snapshots.add(snapshot);
+ } else if (snapshot.operation().equals(DataOperations.OVERWRITE)) {
+ throw new UnsupportedOperationException(
+ String.format("Found %s operation, cannot support incremental data
in snapshots (%s, %s]",
+ DataOperations.OVERWRITE, fromSnapshotId, toSnapshotId));
+ }
+ }
+ return snapshots;
+ }
+
+ public static void validateSnapshotIdsRefinement(long newFromSnapshotId,
long newToSnapshotId, Table table,
+ TableScanContext context) {
+ Set<Long> snapshotIdsRange = Sets.newHashSet(
+ SnapshotUtil.snapshotIdsBetween(table, context.fromSnapshotId(),
context.toSnapshotId()));
Review comment:
This seems like it could make a large set. Is that the case? Is it
avoidable?
##########
File path: core/src/main/java/org/apache/iceberg/util/SnapshotUtil.java
##########
@@ -107,4 +112,47 @@ public static boolean ancestorOf(Table table, long
snapshotId, long ancestorSnap
return newFiles;
}
+
+ public static List<Snapshot> snapshotsWithin(Table table, long
fromSnapshotId, long toSnapshotId) {
+ List<Long> snapshotIds = SnapshotUtil.snapshotIdsBetween(table,
fromSnapshotId, toSnapshotId);
+ List<Snapshot> snapshots = Lists.newArrayList();
+ for (Long snapshotId : snapshotIds) {
+ Snapshot snapshot = table.snapshot(snapshotId);
+ // for now, incremental scan supports only appends
+ if (snapshot.operation().equals(DataOperations.APPEND)) {
+ snapshots.add(snapshot);
+ } else if (snapshot.operation().equals(DataOperations.OVERWRITE)) {
+ throw new UnsupportedOperationException(
+ String.format("Found %s operation, cannot support incremental data
in snapshots (%s, %s]",
+ DataOperations.OVERWRITE, fromSnapshotId, toSnapshotId));
+ }
+ }
+ return snapshots;
+ }
+
+ public static void validateSnapshotIdsRefinement(long newFromSnapshotId,
long newToSnapshotId, Table table,
Review comment:
This is validating that the new from/to is a subset of the current
context range yes?
##########
File path: core/src/main/java/org/apache/iceberg/util/SnapshotUtil.java
##########
@@ -107,4 +112,47 @@ public static boolean ancestorOf(Table table, long
snapshotId, long ancestorSnap
return newFiles;
}
+
+ public static List<Snapshot> snapshotsWithin(Table table, long
fromSnapshotId, long toSnapshotId) {
+ List<Long> snapshotIds = SnapshotUtil.snapshotIdsBetween(table,
fromSnapshotId, toSnapshotId);
+ List<Snapshot> snapshots = Lists.newArrayList();
+ for (Long snapshotId : snapshotIds) {
+ Snapshot snapshot = table.snapshot(snapshotId);
+ // for now, incremental scan supports only appends
+ if (snapshot.operation().equals(DataOperations.APPEND)) {
+ snapshots.add(snapshot);
+ } else if (snapshot.operation().equals(DataOperations.OVERWRITE)) {
+ throw new UnsupportedOperationException(
+ String.format("Found %s operation, cannot support incremental data
in snapshots (%s, %s]",
+ DataOperations.OVERWRITE, fromSnapshotId, toSnapshotId));
+ }
+ }
+ return snapshots;
+ }
+
+ public static void validateSnapshotIdsRefinement(long newFromSnapshotId,
long newToSnapshotId, Table table,
+ TableScanContext context) {
+ Set<Long> snapshotIdsRange = Sets.newHashSet(
+ SnapshotUtil.snapshotIdsBetween(table, context.fromSnapshotId(),
context.toSnapshotId()));
+ // since snapshotIdsBetween return ids in range (fromSnapshotId,
toSnapshotId]
+ snapshotIdsRange.add(context.fromSnapshotId());
+ Preconditions.checkArgument(
+ snapshotIdsRange.contains(newFromSnapshotId),
+ "from snapshot id %s not in existing snapshot ids range (%s, %s]",
+ newFromSnapshotId, context.fromSnapshotId(), newToSnapshotId);
+ Preconditions.checkArgument(
+ snapshotIdsRange.contains(newToSnapshotId),
+ "to snapshot id %s not in existing snapshot ids range (%s, %s]",
+ newToSnapshotId, context.fromSnapshotId(), context.toSnapshotId());
+ }
+
+ public static void validateSnapshotIds(Table table, long fromSnapshotId,
long toSnapshotId) {
Review comment:
This validates the snapshots are present in this table yes?
##########
File path: spark/src/main/java/org/apache/iceberg/actions/PlanScanAction.java
##########
@@ -0,0 +1,268 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.iceberg.actions;
+
+import com.github.benmanes.caffeine.cache.CacheLoader;
+import com.github.benmanes.caffeine.cache.Caffeine;
+import com.github.benmanes.caffeine.cache.LoadingCache;
+import java.io.Serializable;
+import java.util.List;
+import java.util.Map;
+import java.util.stream.Collectors;
+import org.apache.iceberg.BaseFileScanTask;
+import org.apache.iceberg.CombinedScanTask;
+import org.apache.iceberg.DataFile;
+import org.apache.iceberg.DeleteFile;
+import org.apache.iceberg.DeleteFileIndex;
+import org.apache.iceberg.FileScanTask;
+import org.apache.iceberg.HasTableOperations;
+import org.apache.iceberg.ManifestFile;
+import org.apache.iceberg.MetadataTableType;
+import org.apache.iceberg.PartitionSpec;
+import org.apache.iceberg.PartitionSpecParser;
+import org.apache.iceberg.Schema;
+import org.apache.iceberg.SchemaParser;
+import org.apache.iceberg.Snapshot;
+import org.apache.iceberg.Table;
+import org.apache.iceberg.TableOperations;
+import org.apache.iceberg.TableProperties;
+import org.apache.iceberg.TableScanContext;
+import org.apache.iceberg.expressions.Evaluator;
+import org.apache.iceberg.expressions.Expression;
+import org.apache.iceberg.expressions.Expressions;
+import org.apache.iceberg.expressions.InclusiveMetricsEvaluator;
+import org.apache.iceberg.expressions.Projections;
+import org.apache.iceberg.expressions.ResidualEvaluator;
+import org.apache.iceberg.io.CloseableIterable;
+import org.apache.iceberg.relocated.com.google.common.collect.ImmutableMap;
+import org.apache.iceberg.relocated.com.google.common.collect.Streams;
+import org.apache.iceberg.spark.SparkDataFile;
+import org.apache.iceberg.types.Types;
+import org.apache.iceberg.util.SnapshotUtil;
+import org.apache.iceberg.util.TableScanUtil;
+import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.api.java.function.MapPartitionsFunction;
+import org.apache.spark.broadcast.Broadcast;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Row;
+import org.apache.spark.sql.SparkSession;
+import org.apache.spark.sql.catalyst.encoders.RowEncoder;
+import org.apache.spark.sql.types.StructType;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+public class PlanScanAction extends
BaseAction<CloseableIterable<CombinedScanTask>> {
+ public static final String DISTRIBUTED_SCAN_PLANNING =
"iceberg.plan_distributed";
+ private static final Logger LOG =
LoggerFactory.getLogger(PlanScanAction.class);
+
+ private final Table table;
+ private final SparkSession spark;
+ private final JavaSparkContext jsc;
+ private final TableOperations ops;
+ private final Schema schema;
+
+ private TableScanContext context;
+
+ public PlanScanAction(SparkSession spark, Table table) {
+ this.table = table;
+ this.spark = spark;
+ this.jsc = JavaSparkContext.fromSparkContext(spark.sparkContext());
+ this.schema = table.schema();
+ this.ops = ((HasTableOperations) table).operations();
+ this.context = new TableScanContext();
+ }
+
+ public PlanScanAction withContext(TableScanContext newContext) {
+ this.context = newContext;
+ return this;
+ }
+
+ @Override
+ protected Table table() {
+ return table;
+ }
+
+ @Override
+ public CloseableIterable<CombinedScanTask> execute() {
+ LOG.debug("Preparing distributed planning of scan for {}", table);
+ CloseableIterable<CombinedScanTask> result = planTasks();
+ LOG.debug("Planning complete");
+ return result;
+ }
+
+ protected CloseableIterable<CombinedScanTask> planTasks() {
+ Map<String, String> options = context.options();
+ long splitSize;
+ if (options.containsKey(TableProperties.SPLIT_SIZE)) {
+ splitSize = Long.parseLong(options.get(TableProperties.SPLIT_SIZE));
+ } else {
+ splitSize = ops.current().propertyAsLong(TableProperties.SPLIT_SIZE,
TableProperties.SPLIT_SIZE_DEFAULT);
+ }
+ int lookback;
+ if (options.containsKey(TableProperties.SPLIT_LOOKBACK)) {
+ lookback = Integer.parseInt(options.get(TableProperties.SPLIT_LOOKBACK));
+ } else {
+ lookback = ops.current().propertyAsInt(
+ TableProperties.SPLIT_LOOKBACK,
TableProperties.SPLIT_LOOKBACK_DEFAULT);
+ }
+ long openFileCost;
+ if (options.containsKey(TableProperties.SPLIT_OPEN_FILE_COST)) {
+ openFileCost =
Long.parseLong(options.get(TableProperties.SPLIT_OPEN_FILE_COST));
+ } else {
+ openFileCost = ops.current().propertyAsLong(
+ TableProperties.SPLIT_OPEN_FILE_COST,
TableProperties.SPLIT_OPEN_FILE_COST_DEFAULT);
+ }
+
+ CloseableIterable<FileScanTask> fileScanTasks = planFiles();
+ CloseableIterable<FileScanTask> splitFiles =
TableScanUtil.splitFiles(fileScanTasks, splitSize);
+ return TableScanUtil.planTasks(splitFiles, splitSize, lookback,
openFileCost);
+ }
+
+ private Snapshot snapshot() {
+ return context.snapshotId() != null ?
+ ops.current().snapshot(context.snapshotId()) :
+ ops.current().currentSnapshot();
+ }
+
+ public CloseableIterable<FileScanTask> planFiles() {
+ // Create a dataframe of all DataFile entries
+ String dataFilesMetadataTable =
metadataTableName(MetadataTableType.ENTRIES);
+ Dataset<Row> manifestEntries =
+ spark.read()
+ .format("iceberg")
+ .load(dataFilesMetadataTable);
+
+ // Todo pushdown filters to ManifestEntriesTable
+ // Read entries which are not deleted and are datafiles and not delete
files
+ Dataset<Row> dataFileEntries = manifestEntries
+
.filter(manifestEntries.col("data_file").getField(DataFile.CONTENT.name()).equalTo(0))
// Only DataFiles
+ .filter(manifestEntries.col("status").notEqual(2)); // No Deleted Files
+
+ dataFileEntries = handleIncrementalScan(dataFileEntries);
+
+ // Build up evaluators and filters for Metrics and Partition values
+ Expression scanFilter = context.rowFilter();
+ boolean isCaseSensitive = context.caseSensitive();
+
+ // Build cache of partition evaluators
+ Broadcast<Map<Integer, Evaluator>> broadcastPartitionEvaluators =
buildPartitionEvaluators();
+
+ // Build metric evaluators
+ Broadcast<InclusiveMetricsEvaluator> broadcastMetricsEvaluator =
jsc.broadcast(
+ new InclusiveMetricsEvaluator(schema, scanFilter, isCaseSensitive));
+
+ // Cache residual information and Partition spec information
+ Types.StructType partitionStruct =
DataFile.getType(table().spec().partitionType());
+ StructType dataFileSchema = (StructType)
dataFileEntries.schema().apply("data_file").dataType();
+
+ // Evaluate all files based on their partition info and collect the rows
back locally
+ Dataset<Row> scanTaskDataset = dataFileEntries.mapPartitions(
+ (MapPartitionsFunction<Row, Row>) it -> {
+ SparkDataFile container = new SparkDataFile(partitionStruct,
dataFileSchema);
+ return Streams.stream(it)
+ .filter(row -> {
+ Row dataFile = row.getAs("data_file");
+ SparkDataFile file = container.wrap(dataFile);
+ return
broadcastPartitionEvaluators.getValue().get(file.specId()).eval(file.partition())
&&
+ broadcastMetricsEvaluator.getValue().eval(file);
+ }).iterator();
+ }, RowEncoder.apply(dataFileEntries.schema()));
+
+ LoadingCache<Integer, SpecCacheEntry> specCache = buildSpecCache();
+
+ // Build delete index locally
+ DeleteFileIndex deleteFileIndex = buildDeleteFileIndex();
+
+ SparkDataFile container = new SparkDataFile(partitionStruct,
dataFileSchema);
+ List<FileScanTask> tasks =
scanTaskDataset.collectAsList().stream().map(row -> {
+ Row dataFile = row.getAs("data_file");
+ SparkDataFile file = container.wrap(dataFile);
+ DeleteFile[] deletes =
+ deleteFileIndex.forDataFile(row.getAs("sequence_number"), file);
+ SpecCacheEntry cached = specCache.get(file.specId());
+ return (FileScanTask) new BaseFileScanTask(file.copy(), deletes,
cached.schemaString, cached.specString,
+ cached.residuals);
+ }).collect(Collectors.toList());
+
+ return CloseableIterable.withNoopClose(tasks);
+ }
+
+ private Dataset<Row> handleIncrementalScan(Dataset<Row> dataFileEntries) {
+ if (context.fromSnapshotId() != null) {
+ LOG.debug("Planning incremental scan from {} to {}",
context.fromSnapshotId(), context.toSnapshotId());
+ List<Snapshot> snapshots = SnapshotUtil.snapshotsWithin(table,
context.fromSnapshotId(), context.toSnapshotId());
+ List<Long> validSnapshotIds =
snapshots.stream().map(Snapshot::snapshotId).collect(Collectors.toList());
+ return dataFileEntries
+
.filter(dataFileEntries.col("snapshot_id").isin(validSnapshotIds.toArray()))
Review comment:
Could we use a range here to save sending all of the validSnapshotIDs
accross the wire? Or are there going to be intermediate files with snapshotids
we need to exclude?
(I'm assuming we probably need to exclude intermediate files but just making
sure since I'm new to this code).
##########
File path: core/src/main/java/org/apache/iceberg/util/SnapshotUtil.java
##########
@@ -107,4 +112,47 @@ public static boolean ancestorOf(Table table, long
snapshotId, long ancestorSnap
return newFiles;
}
+
+ public static List<Snapshot> snapshotsWithin(Table table, long
fromSnapshotId, long toSnapshotId) {
Review comment:
Might it be good to add some javadoc here? I could see someone calling
this when they really want `snapshotIdsBetween`
##########
File path: spark/src/main/java/org/apache/iceberg/actions/PlanScanAction.java
##########
@@ -0,0 +1,268 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.iceberg.actions;
+
+import com.github.benmanes.caffeine.cache.CacheLoader;
+import com.github.benmanes.caffeine.cache.Caffeine;
+import com.github.benmanes.caffeine.cache.LoadingCache;
+import java.io.Serializable;
+import java.util.List;
+import java.util.Map;
+import java.util.stream.Collectors;
+import org.apache.iceberg.BaseFileScanTask;
+import org.apache.iceberg.CombinedScanTask;
+import org.apache.iceberg.DataFile;
+import org.apache.iceberg.DeleteFile;
+import org.apache.iceberg.DeleteFileIndex;
+import org.apache.iceberg.FileScanTask;
+import org.apache.iceberg.HasTableOperations;
+import org.apache.iceberg.ManifestFile;
+import org.apache.iceberg.MetadataTableType;
+import org.apache.iceberg.PartitionSpec;
+import org.apache.iceberg.PartitionSpecParser;
+import org.apache.iceberg.Schema;
+import org.apache.iceberg.SchemaParser;
+import org.apache.iceberg.Snapshot;
+import org.apache.iceberg.Table;
+import org.apache.iceberg.TableOperations;
+import org.apache.iceberg.TableProperties;
+import org.apache.iceberg.TableScanContext;
+import org.apache.iceberg.expressions.Evaluator;
+import org.apache.iceberg.expressions.Expression;
+import org.apache.iceberg.expressions.Expressions;
+import org.apache.iceberg.expressions.InclusiveMetricsEvaluator;
+import org.apache.iceberg.expressions.Projections;
+import org.apache.iceberg.expressions.ResidualEvaluator;
+import org.apache.iceberg.io.CloseableIterable;
+import org.apache.iceberg.relocated.com.google.common.collect.ImmutableMap;
+import org.apache.iceberg.relocated.com.google.common.collect.Streams;
+import org.apache.iceberg.spark.SparkDataFile;
+import org.apache.iceberg.types.Types;
+import org.apache.iceberg.util.SnapshotUtil;
+import org.apache.iceberg.util.TableScanUtil;
+import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.api.java.function.MapPartitionsFunction;
+import org.apache.spark.broadcast.Broadcast;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Row;
+import org.apache.spark.sql.SparkSession;
+import org.apache.spark.sql.catalyst.encoders.RowEncoder;
+import org.apache.spark.sql.types.StructType;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+public class PlanScanAction extends
BaseAction<CloseableIterable<CombinedScanTask>> {
+ public static final String DISTRIBUTED_SCAN_PLANNING =
"iceberg.plan_distributed";
+ private static final Logger LOG =
LoggerFactory.getLogger(PlanScanAction.class);
+
+ private final Table table;
+ private final SparkSession spark;
+ private final JavaSparkContext jsc;
+ private final TableOperations ops;
+ private final Schema schema;
+
+ private TableScanContext context;
+
+ public PlanScanAction(SparkSession spark, Table table) {
+ this.table = table;
+ this.spark = spark;
+ this.jsc = JavaSparkContext.fromSparkContext(spark.sparkContext());
+ this.schema = table.schema();
+ this.ops = ((HasTableOperations) table).operations();
+ this.context = new TableScanContext();
+ }
+
+ public PlanScanAction withContext(TableScanContext newContext) {
+ this.context = newContext;
+ return this;
+ }
+
+ @Override
+ protected Table table() {
+ return table;
+ }
+
+ @Override
+ public CloseableIterable<CombinedScanTask> execute() {
+ LOG.debug("Preparing distributed planning of scan for {}", table);
+ CloseableIterable<CombinedScanTask> result = planTasks();
+ LOG.debug("Planning complete");
+ return result;
+ }
+
+ protected CloseableIterable<CombinedScanTask> planTasks() {
+ Map<String, String> options = context.options();
+ long splitSize;
+ if (options.containsKey(TableProperties.SPLIT_SIZE)) {
+ splitSize = Long.parseLong(options.get(TableProperties.SPLIT_SIZE));
+ } else {
+ splitSize = ops.current().propertyAsLong(TableProperties.SPLIT_SIZE,
TableProperties.SPLIT_SIZE_DEFAULT);
+ }
+ int lookback;
+ if (options.containsKey(TableProperties.SPLIT_LOOKBACK)) {
+ lookback = Integer.parseInt(options.get(TableProperties.SPLIT_LOOKBACK));
+ } else {
+ lookback = ops.current().propertyAsInt(
+ TableProperties.SPLIT_LOOKBACK,
TableProperties.SPLIT_LOOKBACK_DEFAULT);
+ }
+ long openFileCost;
+ if (options.containsKey(TableProperties.SPLIT_OPEN_FILE_COST)) {
+ openFileCost =
Long.parseLong(options.get(TableProperties.SPLIT_OPEN_FILE_COST));
+ } else {
+ openFileCost = ops.current().propertyAsLong(
+ TableProperties.SPLIT_OPEN_FILE_COST,
TableProperties.SPLIT_OPEN_FILE_COST_DEFAULT);
+ }
+
+ CloseableIterable<FileScanTask> fileScanTasks = planFiles();
+ CloseableIterable<FileScanTask> splitFiles =
TableScanUtil.splitFiles(fileScanTasks, splitSize);
+ return TableScanUtil.planTasks(splitFiles, splitSize, lookback,
openFileCost);
+ }
+
+ private Snapshot snapshot() {
+ return context.snapshotId() != null ?
+ ops.current().snapshot(context.snapshotId()) :
+ ops.current().currentSnapshot();
+ }
+
+ public CloseableIterable<FileScanTask> planFiles() {
+ // Create a dataframe of all DataFile entries
+ String dataFilesMetadataTable =
metadataTableName(MetadataTableType.ENTRIES);
+ Dataset<Row> manifestEntries =
+ spark.read()
+ .format("iceberg")
+ .load(dataFilesMetadataTable);
+
+ // Todo pushdown filters to ManifestEntriesTable
+ // Read entries which are not deleted and are datafiles and not delete
files
+ Dataset<Row> dataFileEntries = manifestEntries
+
.filter(manifestEntries.col("data_file").getField(DataFile.CONTENT.name()).equalTo(0))
// Only DataFiles
+ .filter(manifestEntries.col("status").notEqual(2)); // No Deleted Files
Review comment:
Are there enums of these somewhere?
##########
File path: spark/src/main/java/org/apache/iceberg/actions/PlanScanAction.java
##########
@@ -0,0 +1,268 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.iceberg.actions;
+
+import com.github.benmanes.caffeine.cache.CacheLoader;
+import com.github.benmanes.caffeine.cache.Caffeine;
+import com.github.benmanes.caffeine.cache.LoadingCache;
+import java.io.Serializable;
+import java.util.List;
+import java.util.Map;
+import java.util.stream.Collectors;
+import org.apache.iceberg.BaseFileScanTask;
+import org.apache.iceberg.CombinedScanTask;
+import org.apache.iceberg.DataFile;
+import org.apache.iceberg.DeleteFile;
+import org.apache.iceberg.DeleteFileIndex;
+import org.apache.iceberg.FileScanTask;
+import org.apache.iceberg.HasTableOperations;
+import org.apache.iceberg.ManifestFile;
+import org.apache.iceberg.MetadataTableType;
+import org.apache.iceberg.PartitionSpec;
+import org.apache.iceberg.PartitionSpecParser;
+import org.apache.iceberg.Schema;
+import org.apache.iceberg.SchemaParser;
+import org.apache.iceberg.Snapshot;
+import org.apache.iceberg.Table;
+import org.apache.iceberg.TableOperations;
+import org.apache.iceberg.TableProperties;
+import org.apache.iceberg.TableScanContext;
+import org.apache.iceberg.expressions.Evaluator;
+import org.apache.iceberg.expressions.Expression;
+import org.apache.iceberg.expressions.Expressions;
+import org.apache.iceberg.expressions.InclusiveMetricsEvaluator;
+import org.apache.iceberg.expressions.Projections;
+import org.apache.iceberg.expressions.ResidualEvaluator;
+import org.apache.iceberg.io.CloseableIterable;
+import org.apache.iceberg.relocated.com.google.common.collect.ImmutableMap;
+import org.apache.iceberg.relocated.com.google.common.collect.Streams;
+import org.apache.iceberg.spark.SparkDataFile;
+import org.apache.iceberg.types.Types;
+import org.apache.iceberg.util.SnapshotUtil;
+import org.apache.iceberg.util.TableScanUtil;
+import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.api.java.function.MapPartitionsFunction;
+import org.apache.spark.broadcast.Broadcast;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Row;
+import org.apache.spark.sql.SparkSession;
+import org.apache.spark.sql.catalyst.encoders.RowEncoder;
+import org.apache.spark.sql.types.StructType;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+public class PlanScanAction extends
BaseAction<CloseableIterable<CombinedScanTask>> {
+ public static final String DISTRIBUTED_SCAN_PLANNING =
"iceberg.plan_distributed";
+ private static final Logger LOG =
LoggerFactory.getLogger(PlanScanAction.class);
+
+ private final Table table;
+ private final SparkSession spark;
+ private final JavaSparkContext jsc;
+ private final TableOperations ops;
+ private final Schema schema;
+
+ private TableScanContext context;
+
+ public PlanScanAction(SparkSession spark, Table table) {
+ this.table = table;
+ this.spark = spark;
+ this.jsc = JavaSparkContext.fromSparkContext(spark.sparkContext());
+ this.schema = table.schema();
+ this.ops = ((HasTableOperations) table).operations();
+ this.context = new TableScanContext();
+ }
+
+ public PlanScanAction withContext(TableScanContext newContext) {
+ this.context = newContext;
+ return this;
+ }
+
+ @Override
+ protected Table table() {
+ return table;
+ }
+
+ @Override
+ public CloseableIterable<CombinedScanTask> execute() {
+ LOG.debug("Preparing distributed planning of scan for {}", table);
+ CloseableIterable<CombinedScanTask> result = planTasks();
+ LOG.debug("Planning complete");
+ return result;
+ }
+
+ protected CloseableIterable<CombinedScanTask> planTasks() {
+ Map<String, String> options = context.options();
+ long splitSize;
+ if (options.containsKey(TableProperties.SPLIT_SIZE)) {
+ splitSize = Long.parseLong(options.get(TableProperties.SPLIT_SIZE));
+ } else {
+ splitSize = ops.current().propertyAsLong(TableProperties.SPLIT_SIZE,
TableProperties.SPLIT_SIZE_DEFAULT);
+ }
+ int lookback;
+ if (options.containsKey(TableProperties.SPLIT_LOOKBACK)) {
+ lookback = Integer.parseInt(options.get(TableProperties.SPLIT_LOOKBACK));
+ } else {
+ lookback = ops.current().propertyAsInt(
+ TableProperties.SPLIT_LOOKBACK,
TableProperties.SPLIT_LOOKBACK_DEFAULT);
+ }
+ long openFileCost;
+ if (options.containsKey(TableProperties.SPLIT_OPEN_FILE_COST)) {
+ openFileCost =
Long.parseLong(options.get(TableProperties.SPLIT_OPEN_FILE_COST));
+ } else {
+ openFileCost = ops.current().propertyAsLong(
+ TableProperties.SPLIT_OPEN_FILE_COST,
TableProperties.SPLIT_OPEN_FILE_COST_DEFAULT);
+ }
+
+ CloseableIterable<FileScanTask> fileScanTasks = planFiles();
+ CloseableIterable<FileScanTask> splitFiles =
TableScanUtil.splitFiles(fileScanTasks, splitSize);
+ return TableScanUtil.planTasks(splitFiles, splitSize, lookback,
openFileCost);
+ }
+
+ private Snapshot snapshot() {
+ return context.snapshotId() != null ?
+ ops.current().snapshot(context.snapshotId()) :
+ ops.current().currentSnapshot();
+ }
+
+ public CloseableIterable<FileScanTask> planFiles() {
+ // Create a dataframe of all DataFile entries
+ String dataFilesMetadataTable =
metadataTableName(MetadataTableType.ENTRIES);
+ Dataset<Row> manifestEntries =
+ spark.read()
+ .format("iceberg")
+ .load(dataFilesMetadataTable);
+
+ // Todo pushdown filters to ManifestEntriesTable
+ // Read entries which are not deleted and are datafiles and not delete
files
+ Dataset<Row> dataFileEntries = manifestEntries
+
.filter(manifestEntries.col("data_file").getField(DataFile.CONTENT.name()).equalTo(0))
// Only DataFiles
+ .filter(manifestEntries.col("status").notEqual(2)); // No Deleted Files
+
+ dataFileEntries = handleIncrementalScan(dataFileEntries);
+
+ // Build up evaluators and filters for Metrics and Partition values
+ Expression scanFilter = context.rowFilter();
+ boolean isCaseSensitive = context.caseSensitive();
+
+ // Build cache of partition evaluators
+ Broadcast<Map<Integer, Evaluator>> broadcastPartitionEvaluators =
buildPartitionEvaluators();
+
+ // Build metric evaluators
+ Broadcast<InclusiveMetricsEvaluator> broadcastMetricsEvaluator =
jsc.broadcast(
+ new InclusiveMetricsEvaluator(schema, scanFilter, isCaseSensitive));
+
+ // Cache residual information and Partition spec information
+ Types.StructType partitionStruct =
DataFile.getType(table().spec().partitionType());
+ StructType dataFileSchema = (StructType)
dataFileEntries.schema().apply("data_file").dataType();
+
+ // Evaluate all files based on their partition info and collect the rows
back locally
+ Dataset<Row> scanTaskDataset = dataFileEntries.mapPartitions(
+ (MapPartitionsFunction<Row, Row>) it -> {
+ SparkDataFile container = new SparkDataFile(partitionStruct,
dataFileSchema);
+ return Streams.stream(it)
+ .filter(row -> {
+ Row dataFile = row.getAs("data_file");
+ SparkDataFile file = container.wrap(dataFile);
+ return
broadcastPartitionEvaluators.getValue().get(file.specId()).eval(file.partition())
&&
+ broadcastMetricsEvaluator.getValue().eval(file);
+ }).iterator();
+ }, RowEncoder.apply(dataFileEntries.schema()));
+
+ LoadingCache<Integer, SpecCacheEntry> specCache = buildSpecCache();
+
+ // Build delete index locally
+ DeleteFileIndex deleteFileIndex = buildDeleteFileIndex();
+
+ SparkDataFile container = new SparkDataFile(partitionStruct,
dataFileSchema);
+ List<FileScanTask> tasks =
scanTaskDataset.collectAsList().stream().map(row -> {
+ Row dataFile = row.getAs("data_file");
+ SparkDataFile file = container.wrap(dataFile);
+ DeleteFile[] deletes =
+ deleteFileIndex.forDataFile(row.getAs("sequence_number"), file);
+ SpecCacheEntry cached = specCache.get(file.specId());
+ return (FileScanTask) new BaseFileScanTask(file.copy(), deletes,
cached.schemaString, cached.specString,
+ cached.residuals);
+ }).collect(Collectors.toList());
+
+ return CloseableIterable.withNoopClose(tasks);
+ }
+
+ private Dataset<Row> handleIncrementalScan(Dataset<Row> dataFileEntries) {
+ if (context.fromSnapshotId() != null) {
+ LOG.debug("Planning incremental scan from {} to {}",
context.fromSnapshotId(), context.toSnapshotId());
+ List<Snapshot> snapshots = SnapshotUtil.snapshotsWithin(table,
context.fromSnapshotId(), context.toSnapshotId());
+ List<Long> validSnapshotIds =
snapshots.stream().map(Snapshot::snapshotId).collect(Collectors.toList());
+ return dataFileEntries
+
.filter(dataFileEntries.col("snapshot_id").isin(validSnapshotIds.toArray()))
+ .filter(dataFileEntries.col("status").equalTo(1)); // Added files
only
Review comment:
enum?
##########
File path: core/src/main/java/org/apache/iceberg/util/TableScanUtil.java
##########
@@ -57,4 +57,6 @@ public static boolean hasDeletes(FileScanTask task) {
splitFiles),
BaseCombinedScanTask::new);
}
+
Review comment:
Is this intentional?
##########
File path: spark/src/main/java/org/apache/iceberg/actions/PlanScanAction.java
##########
@@ -0,0 +1,271 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.iceberg.actions;
+
+import com.github.benmanes.caffeine.cache.CacheLoader;
+import com.github.benmanes.caffeine.cache.Caffeine;
+import com.github.benmanes.caffeine.cache.LoadingCache;
+import java.io.Serializable;
+import java.util.List;
+import java.util.Map;
+import java.util.stream.Collectors;
+import org.apache.iceberg.BaseFileScanTask;
+import org.apache.iceberg.BaseTableScan;
+import org.apache.iceberg.CombinedScanTask;
+import org.apache.iceberg.DataFile;
+import org.apache.iceberg.DataTableScan;
+import org.apache.iceberg.DeleteFile;
+import org.apache.iceberg.DeleteFileIndex;
+import org.apache.iceberg.FileScanTask;
+import org.apache.iceberg.IncrementalDataTableScan;
+import org.apache.iceberg.ManifestFile;
+import org.apache.iceberg.MetadataTableType;
+import org.apache.iceberg.PartitionSpec;
+import org.apache.iceberg.PartitionSpecParser;
+import org.apache.iceberg.SchemaParser;
+import org.apache.iceberg.Snapshot;
+import org.apache.iceberg.Table;
+import org.apache.iceberg.TableMetadata;
+import org.apache.iceberg.TableProperties;
+import org.apache.iceberg.TableScan;
+import org.apache.iceberg.events.Listeners;
+import org.apache.iceberg.events.ScanEvent;
+import org.apache.iceberg.expressions.Evaluator;
+import org.apache.iceberg.expressions.Expression;
+import org.apache.iceberg.expressions.Expressions;
+import org.apache.iceberg.expressions.InclusiveMetricsEvaluator;
+import org.apache.iceberg.expressions.Projections;
+import org.apache.iceberg.expressions.ResidualEvaluator;
+import org.apache.iceberg.io.CloseableIterable;
+import org.apache.iceberg.relocated.com.google.common.collect.ImmutableMap;
+import org.apache.iceberg.relocated.com.google.common.collect.Streams;
+import org.apache.iceberg.spark.SparkDataFile;
+import org.apache.iceberg.types.Types;
+import org.apache.iceberg.util.TableScanUtil;
+import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.api.java.function.MapPartitionsFunction;
+import org.apache.spark.broadcast.Broadcast;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Row;
+import org.apache.spark.sql.SparkSession;
+import org.apache.spark.sql.catalyst.encoders.RowEncoder;
+import org.apache.spark.sql.types.StructType;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+public class PlanScanAction extends
BaseAction<CloseableIterable<CombinedScanTask>> {
+ private static final Logger LOG =
LoggerFactory.getLogger(PlanScanAction.class);
+ private static final Types.StructType EMPTY_STRUCT = Types.StructType.of();
+
+ private final Table table;
+ private final TableScan scan;
+ private final SparkSession spark;
+ private final Snapshot snapshot;
+
+ private PlanScanAction(SparkSession spark, Table table, TableScan scan) {
+ this.spark = spark;
+ this.table = table;
+ this.scan = scan;
+ this.snapshot = scan.snapshot();
+ }
+
+ public PlanScanAction(SparkSession spark, Table table, DataTableScan scan) {
+ this(spark, table, (TableScan) scan);
+ }
+
+ @Override
+ protected Table table() {
+ return table;
+ }
+
+ @Override
+ public CloseableIterable<CombinedScanTask> execute() {
+ Map<String, String> options = ((BaseTableScan) scan).options();
+ TableMetadata meta = ((BaseTableScan) scan).tableOps().current(); // TODO
maybe pass through metadata instead
+ long splitSize;
+ if (options.containsKey(TableProperties.SPLIT_SIZE)) {
+ splitSize = Long.parseLong(options.get(TableProperties.SPLIT_SIZE));
+ } else {
+ splitSize = meta.propertyAsLong(TableProperties.SPLIT_SIZE,
TableProperties.SPLIT_SIZE_DEFAULT);
+ }
+ int lookback;
+ if (options.containsKey(TableProperties.SPLIT_LOOKBACK)) {
+ lookback = Integer.parseInt(options.get(TableProperties.SPLIT_LOOKBACK));
+ } else {
+ lookback = meta.propertyAsInt(TableProperties.SPLIT_LOOKBACK,
TableProperties.SPLIT_LOOKBACK_DEFAULT);
+ }
+ long openFileCost;
+ if (options.containsKey(TableProperties.SPLIT_OPEN_FILE_COST)) {
+ openFileCost =
Long.parseLong(options.get(TableProperties.SPLIT_OPEN_FILE_COST));
+ } else {
+ openFileCost = meta.propertyAsLong(
+ TableProperties.SPLIT_OPEN_FILE_COST,
TableProperties.SPLIT_OPEN_FILE_COST_DEFAULT);
+ }
+
+ CloseableIterable<FileScanTask> fileScanTasks = planFiles();
+ CloseableIterable<FileScanTask> splitFiles =
TableScanUtil.splitFiles(fileScanTasks, splitSize);
+ return TableScanUtil.planTasks(splitFiles, splitSize, lookback,
openFileCost);
+ }
+
+ private CloseableIterable<FileScanTask> planFiles() {
+ if (snapshot != null) {
+ LOG.info("Distributed Scanning table {} snapshot {} created at {} with
filter {}", scan.table(),
+ snapshot.snapshotId(), snapshot.timestampMillis(), scan.filter());
+ Listeners.notifyAll(
+ new ScanEvent(scan.table().toString(), snapshot.snapshotId(),
scan.filter(), scan.schema()));
+ return planFilesFor();
+ } else {
+ LOG.info("Scanning empty table {}", scan.table());
+ return CloseableIterable.empty();
+ }
+ }
+
+ private CloseableIterable<FileScanTask> planFilesFor() {
+ // This is different for different BaseTableScan implementations
+ if (scan instanceof DataTableScan) {
+ return planDataTableScanFiles();
+ } else {
+ throw new UnsupportedOperationException(String.format("Unable to do
distributed planning for %s",
+ scan.getClass()));
+ }
+ }
+
+ private DeleteFileIndex buildDeleteFileIndex() {
+ // Build delete index locally
+ List<ManifestFile> deleteManifests = snapshot.deleteManifests();
+ DeleteFileIndex.Builder deleteFileIndexBuilder =
DeleteFileIndex.builderFor(table.io(), deleteManifests);
+ deleteFileIndexBuilder.caseSensitive(scan.isCaseSensitive());
+ deleteFileIndexBuilder.specsById(table.specs());
+ deleteFileIndexBuilder.filterData(scan.filter());
+ return deleteFileIndexBuilder.build();
+ }
+
+ private CloseableIterable<FileScanTask> planDataTableScanFiles() {
+ // TODO Currently this approach reads all manifests, no manifest filtering
- Maybe through pushdowns or table read
+ // options?
+
+
+ // Create a dataframe of all DataFile entries
+ String dataFilesMetadataTable =
metadataTableName(MetadataTableType.ENTRIES);
+ Dataset<Row> manifestEntries =
+ spark.read()
+ .format("iceberg")
+ .load(dataFilesMetadataTable);
+
+ // Todo pushdown filters to ManifestEntriesTable
+ // Read entries which are not deleted and are datafiles and not delete
files
+ Dataset<Row> dataFileEntries =
+
manifestEntries.filter(manifestEntries.col("data_file").getField(DataFile.CONTENT.name()).equalTo(0))
+ .filter(manifestEntries.col("status").notEqual(2)); // not deleted
+
+ if (scan instanceof IncrementalDataTableScan) {
+ IncrementalDataTableScan incScan = (IncrementalDataTableScan) scan;
+ List<Snapshot> snapshots =
IncrementalDataTableScan.snapshotsWithin(table, incScan.fromSnapshotId(),
+ incScan.toSnapshotId());
+ List<Long> validSnapshotIds =
snapshots.stream().map(Snapshot::snapshotId).collect(Collectors.toList());
+ dataFileEntries =
dataFileEntries.filter(dataFileEntries.col("snapshot_id")
+ .isin(validSnapshotIds.toArray()));
+ }
+
+ final Expression scanFilter = scan.filter();
+ final boolean ignoreResiduals = scan.shouldIgnoreResiduals();
+ final boolean isCaseSensitive = scan.isCaseSensitive();
+
+ Map<Integer, PartitionSpec> specsById = scan.table().specs();
+ JavaSparkContext jsc =
JavaSparkContext.fromSparkContext(spark.sparkContext());
+
+ /*
+ Since we aren't filtering entries on manifest read, filter file entries
using Partition information
+ In the normal path this happens with the manifest reader's entries code,
filtering elements before we
+ get to this stage.
+ */
+
+ // Build cache of partition evaluators
+ ImmutableMap.Builder<Integer, Evaluator> evalMapBuilder =
ImmutableMap.builder();
+ specsById.entrySet().stream().forEach(entry ->
+ evalMapBuilder.put(entry.getKey(),
+ new Evaluator(entry.getValue().partitionType(),
+ Projections.inclusive(entry.getValue(),
isCaseSensitive).project(scanFilter))));
+
+ Map<Integer, Evaluator> partitionEvaluatorsById = evalMapBuilder.build();
+ Broadcast<Map<Integer, Evaluator>> broadcastPartitionEvaluators =
jsc.broadcast(partitionEvaluatorsById);
+
+ Broadcast<InclusiveMetricsEvaluator> broadcastMetricsEvaluator =
jsc.broadcast(
+ new InclusiveMetricsEvaluator(scan.schema(), scanFilter,
isCaseSensitive));
+
+ // Cache residual information and Partition spec information
+ final Broadcast<Map<Integer, PartitionSpec>> broadcastSpecsById =
jsc.broadcast(specsById);
+
+ Types.StructType partitionStruct =
DataFile.getType(scan.table().spec().partitionType());
+ StructType dataFileSchema = (StructType)
dataFileEntries.schema().apply("data_file").dataType();
+
+ // Evaluate all files based on their partition info and collect the rows
back locally
+ Dataset<Row> scanTaskDataset = dataFileEntries.mapPartitions(
+ (MapPartitionsFunction<Row, Row>) it -> {
+ SparkDataFile container = new SparkDataFile(partitionStruct,
dataFileSchema);
+ return Streams.stream(it)
+ .filter(row -> {
+ Row dataFile = row.getAs("data_file");
+ SparkDataFile file = container.wrap(dataFile);
+ return
broadcastPartitionEvaluators.getValue().get(file.specId()).eval(file.partition())
&&
+ broadcastMetricsEvaluator.getValue().eval(file);
+ }).iterator();
+ }, RowEncoder.apply(dataFileEntries.schema()));
+
+ LoadingCache<Integer, SpecCacheEntry> specCache =
+ Caffeine.newBuilder().build((CacheLoader<Integer, SpecCacheEntry> &
Serializable) specId -> {
+ PartitionSpec spec = broadcastSpecsById.getValue().get(specId);
+ Expression filter = ignoreResiduals ? Expressions.alwaysTrue() :
scanFilter;
+ return new SpecCacheEntry(SchemaParser.toJson(spec.schema()),
PartitionSpecParser.toJson(spec),
+ ResidualEvaluator.of(spec, filter, isCaseSensitive));
+ });
+
+ // Build delete index locally
+ DeleteFileIndex deleteFileIndex = buildDeleteFileIndex();
+ SparkDataFile container = new SparkDataFile(partitionStruct,
dataFileSchema);
+ List<FileScanTask> tasks =
scanTaskDataset.collectAsList().stream().map(row -> {
Review comment:
scnaTaskDataset is always going to be relatively small in return value
right?
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