[GitHub] [iceberg] aokolnychyi commented on a change in pull request #2361: Spark: Refactor action for rewriting manifests

[GitBox <gi...@apache.org>]

aokolnychyi commented on a change in pull request #2361:
URL: https://github.com/apache/iceberg/pull/2361#discussion_r600213324



##########
File path: spark/src/main/java/org/apache/iceberg/spark/actions/BaseRewriteManifestsSparkAction.java
##########
@@ -0,0 +1,369 @@
+/*
+ * 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.spark.actions;
+
+import java.io.IOException;
+import java.util.Collections;
+import java.util.List;
+import java.util.UUID;
+import java.util.function.Function;
+import java.util.function.Predicate;
+import java.util.stream.Collectors;
+import org.apache.hadoop.fs.Path;
+import org.apache.iceberg.DataFile;
+import org.apache.iceberg.FileFormat;
+import org.apache.iceberg.HasTableOperations;
+import org.apache.iceberg.ManifestFile;
+import org.apache.iceberg.ManifestFiles;
+import org.apache.iceberg.ManifestWriter;
+import org.apache.iceberg.PartitionSpec;
+import org.apache.iceberg.Snapshot;
+import org.apache.iceberg.Table;
+import org.apache.iceberg.TableOperations;
+import org.apache.iceberg.TableProperties;
+import org.apache.iceberg.actions.BaseRewriteManifestsActionResult;
+import org.apache.iceberg.actions.RewriteManifests;
+import org.apache.iceberg.exceptions.ValidationException;
+import org.apache.iceberg.io.FileIO;
+import org.apache.iceberg.io.OutputFile;
+import org.apache.iceberg.relocated.com.google.common.base.Preconditions;
+import org.apache.iceberg.relocated.com.google.common.collect.ImmutableList;
+import org.apache.iceberg.relocated.com.google.common.collect.Iterables;
+import org.apache.iceberg.relocated.com.google.common.collect.Lists;
+import org.apache.iceberg.spark.JobGroupInfo;
+import org.apache.iceberg.spark.SparkDataFile;
+import org.apache.iceberg.spark.SparkUtil;
+import org.apache.iceberg.types.Types;
+import org.apache.iceberg.util.PropertyUtil;
+import org.apache.iceberg.util.Tasks;
+import org.apache.spark.api.java.function.MapFunction;
+import org.apache.spark.api.java.function.MapPartitionsFunction;
+import org.apache.spark.broadcast.Broadcast;
+import org.apache.spark.sql.Column;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Encoder;
+import org.apache.spark.sql.Encoders;
+import org.apache.spark.sql.Row;
+import org.apache.spark.sql.SparkSession;
+import org.apache.spark.sql.internal.SQLConf;
+import org.apache.spark.sql.types.StructType;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import static org.apache.iceberg.MetadataTableType.ENTRIES;
+
+/**
+ * An action that rewrites manifests in a distributed manner and co-locates metadata for partitions.
+ * <p>
+ * By default, this action rewrites all manifests for the current partition spec and writes the result
+ * to the metadata folder. The behavior can be modified by passing a custom predicate to {@link #rewriteIf(Predicate)}
+ * and a custom spec id to {@link #specId(int)}. In addition, there is a way to configure a custom location
+ * for new manifests via {@link #stagingLocation}.
+ */
+public class BaseRewriteManifestsSparkAction
+    extends BaseSnapshotUpdateSparkAction<RewriteManifests, RewriteManifests.Result>
+    implements RewriteManifests {
+
+  private static final Logger LOG = LoggerFactory.getLogger(BaseRewriteManifestsSparkAction.class);
+
+  private final Encoder<ManifestFile> manifestEncoder;
+  private final Table table;
+  private final int formatVersion;
+  private final FileIO fileIO;
+  private final long targetManifestSizeBytes;
+
+  private PartitionSpec spec = null;
+  private Predicate<ManifestFile> predicate = manifest -> true;
+  private String stagingLocation = null;
+
+  public BaseRewriteManifestsSparkAction(SparkSession spark, Table table) {
+    super(spark);
+    this.manifestEncoder = Encoders.javaSerialization(ManifestFile.class);
+    this.table = table;
+    this.spec = table.spec();
+    this.targetManifestSizeBytes = PropertyUtil.propertyAsLong(
+        table.properties(),
+        TableProperties.MANIFEST_TARGET_SIZE_BYTES,
+        TableProperties.MANIFEST_TARGET_SIZE_BYTES_DEFAULT);
+    this.fileIO = SparkUtil.serializableFileIO(table);
+
+    // default the staging location to the metadata location
+    TableOperations ops = ((HasTableOperations) table).operations();
+    Path metadataFilePath = new Path(ops.metadataFileLocation("file"));
+    this.stagingLocation = metadataFilePath.getParent().toString();
+
+    // use the current table format version for new manifests
+    this.formatVersion = ops.current().formatVersion();
+  }
+
+  @Override
+  protected RewriteManifests self() {
+    return this;
+  }
+
+  public RewriteManifests specId(int specId) {
+    Preconditions.checkArgument(table.specs().containsKey(specId), "Invalid spec id %d", specId);
+    this.spec = table.specs().get(specId);
+    return this;
+  }
+
+  /**
+   * Rewrites only manifests that match the given predicate.
+   *
+   * @param newPredicate a predicate
+   * @return this for method chaining
+   */
+  public RewriteManifests rewriteIf(Predicate<ManifestFile> newPredicate) {
+    this.predicate = newPredicate;
+    return this;
+  }
+
+  /**
+   * Passes a location where the manifests should be written.
+   *
+   * @param newStagingLocation a staging location
+   * @return this for method chaining
+   */
+  public RewriteManifests stagingLocation(String newStagingLocation) {
+    this.stagingLocation = newStagingLocation;
+    return this;
+  }
+
+  @Override
+  public RewriteManifests.Result execute() {
+    JobGroupInfo info = newJobGroupInfo("REWRITE-MANIFESTS", "REWRITE-MANIFESTS");
+    return withJobGroupInfo(info, this::doExecute);
+  }
+
+  private RewriteManifests.Result doExecute() {
+    List<ManifestFile> matchingManifests = findMatchingManifests();
+    if (matchingManifests.isEmpty()) {
+      return BaseRewriteManifestsActionResult.empty();
+    }
+
+    long totalSizeBytes = 0L;
+    int numEntries = 0;
+
+    for (ManifestFile manifest : matchingManifests) {
+      ValidationException.check(hasFileCounts(manifest), "No file counts in manifest: %s", manifest.path());
+
+      totalSizeBytes += manifest.length();
+      numEntries += manifest.addedFilesCount() + manifest.existingFilesCount() + manifest.deletedFilesCount();
+    }
+
+    int targetNumManifests = targetNumManifests(totalSizeBytes);
+    int targetNumManifestEntries = targetNumManifestEntries(numEntries, targetNumManifests);
+
+    Dataset<Row> manifestEntryDF = buildManifestEntryDF(matchingManifests);
+
+    List<ManifestFile> newManifests;
+    if (spec.fields().size() < 1) {
+      newManifests = writeManifestsForUnpartitionedTable(manifestEntryDF, targetNumManifests);
+    } else {
+      newManifests = writeManifestsForPartitionedTable(manifestEntryDF, targetNumManifests, targetNumManifestEntries);
+    }
+
+    replaceManifests(matchingManifests, newManifests);
+
+    return new BaseRewriteManifestsActionResult(matchingManifests, newManifests);
+  }
+
+  private Dataset<Row> buildManifestEntryDF(List<ManifestFile> manifests) {
+    Dataset<Row> manifestDF = spark()
+        .createDataset(Lists.transform(manifests, ManifestFile::path), Encoders.STRING())
+        .toDF("manifest");
+
+    Dataset<Row> manifestEntryDF = loadMetadataTable(table, ENTRIES)
+        .filter("status < 2") // select only live entries
+        .selectExpr("input_file_name() as manifest", "snapshot_id", "sequence_number", "data_file");
+
+    Column joinCond = manifestDF.col("manifest").equalTo(manifestEntryDF.col("manifest"));
+    return manifestEntryDF
+        .join(manifestDF, joinCond, "left_semi")
+        .select("snapshot_id", "sequence_number", "data_file");
+  }
+
+  private List<ManifestFile> writeManifestsForUnpartitionedTable(Dataset<Row> manifestEntryDF, int numManifests) {
+    Broadcast<FileIO> io = sparkContext().broadcast(fileIO);
+    StructType sparkType = (StructType) manifestEntryDF.schema().apply("data_file").dataType();
+
+    // we rely only on the target number of manifests for unpartitioned tables
+    // as we should not worry about having too much metadata per partition
+    long maxNumManifestEntries = Long.MAX_VALUE;
+
+    return manifestEntryDF
+        .repartition(numManifests)
+        .mapPartitions(
+            toManifests(io, maxNumManifestEntries, stagingLocation, formatVersion, spec, sparkType),
+            manifestEncoder
+        )
+        .collectAsList();
+  }
+
+  private List<ManifestFile> writeManifestsForPartitionedTable(
+      Dataset<Row> manifestEntryDF, int numManifests,
+      int targetNumManifestEntries) {
+
+    Broadcast<FileIO> io = sparkContext().broadcast(fileIO);
+    StructType sparkType = (StructType) manifestEntryDF.schema().apply("data_file").dataType();
+
+    // we allow the actual size of manifests to be 10% higher if the estimation is not precise enough
+    long maxNumManifestEntries = (long) (1.1 * targetNumManifestEntries);
+
+    return withReusableDS(manifestEntryDF, df -> {
+      Column partitionColumn = df.col("data_file.partition");
+      return df.repartitionByRange(numManifests, partitionColumn)
+          .sortWithinPartitions(partitionColumn)
+          .mapPartitions(
+              toManifests(io, maxNumManifestEntries, stagingLocation, formatVersion, spec, sparkType),
+              manifestEncoder
+          )
+          .collectAsList();
+    });
+  }
+
+  private <T, U> U withReusableDS(Dataset<T> ds, Function<Dataset<T>, U> func) {
+    Dataset<T> reusableDS;
+    boolean useCaching = PropertyUtil.propertyAsBoolean(options(), "use-caching", true);
+    if (useCaching) {
+      reusableDS = ds.cache();
+    } else {
+      int parallelism = SQLConf.get().numShufflePartitions();
+      reusableDS = ds.repartition(parallelism).map((MapFunction<T, T>) value -> value, ds.exprEnc());
+    }
+
+    try {
+      return func.apply(reusableDS);
+    } finally {
+      if (useCaching) {
+        reusableDS.unpersist(false);
+      }
+    }
+  }
+
+  private List<ManifestFile> findMatchingManifests() {
+    Snapshot currentSnapshot = table.currentSnapshot();
+
+    if (currentSnapshot == null) {
+      return ImmutableList.of();
+    }
+
+    return currentSnapshot.dataManifests().stream()
+        .filter(manifest -> manifest.partitionSpecId() == spec.specId() && predicate.test(manifest))
+        .collect(Collectors.toList());
+  }
+
+  private int targetNumManifests(long totalSizeBytes) {
+    return (int) ((totalSizeBytes + targetManifestSizeBytes - 1) / targetManifestSizeBytes);
+  }
+
+  private int targetNumManifestEntries(int numEntries, int numManifests) {
+    return (numEntries + numManifests - 1) / numManifests;
+  }
+
+  private boolean hasFileCounts(ManifestFile manifest) {
+    return manifest.addedFilesCount() != null &&
+        manifest.existingFilesCount() != null &&
+        manifest.deletedFilesCount() != null;
+  }
+
+  private void replaceManifests(Iterable<ManifestFile> deletedManifests, Iterable<ManifestFile> addedManifests) {
+    try {
+      boolean snapshotIdInheritanceEnabled = PropertyUtil.propertyAsBoolean(
+          table.properties(),
+          TableProperties.SNAPSHOT_ID_INHERITANCE_ENABLED,
+          TableProperties.SNAPSHOT_ID_INHERITANCE_ENABLED_DEFAULT);
+
+      org.apache.iceberg.RewriteManifests rewriteManifests = table.rewriteManifests();
+      deletedManifests.forEach(rewriteManifests::deleteManifest);
+      addedManifests.forEach(rewriteManifests::addManifest);
+      commit(rewriteManifests);
+
+      if (!snapshotIdInheritanceEnabled) {
+        // delete new manifests as they were rewritten before the commit
+        deleteFiles(Iterables.transform(addedManifests, ManifestFile::path));
+      }
+    } catch (Exception e) {
+      // delete all new manifests because the rewrite failed
+      deleteFiles(Iterables.transform(addedManifests, ManifestFile::path));
+      throw e;
+    }
+  }
+
+  private void deleteFiles(Iterable<String> locations) {
+    Tasks.foreach(locations)
+        .noRetry()
+        .suppressFailureWhenFinished()
+        .onFailure((location, exc) -> LOG.warn("Failed to delete: {}", location, exc))
+        .run(fileIO::deleteFile);
+  }
+
+  private static ManifestFile writeManifest(
+      List<Row> rows, int startIndex, int endIndex, Broadcast<FileIO> io,
+      String location, int format, PartitionSpec spec, StructType sparkType) throws IOException {
+
+    String manifestName = "optimized-m-" + UUID.randomUUID();
+    Path manifestPath = new Path(location, manifestName);
+    OutputFile outputFile = io.value().newOutputFile(FileFormat.AVRO.addExtension(manifestPath.toString()));
+
+    Types.StructType dataFileType = DataFile.getType(spec.partitionType());
+    SparkDataFile wrapper = new SparkDataFile(dataFileType, sparkType);
+
+    ManifestWriter<DataFile> writer = ManifestFiles.write(format, spec, outputFile, null);
+
+    try {
+      for (int index = startIndex; index < endIndex; index++) {
+        Row row = rows.get(index);
+        long snapshotId = row.getLong(0);
+        long sequenceNumber = row.getLong(1);
+        Row file = row.getStruct(2);
+        writer.existing(wrapper.wrap(file), snapshotId, sequenceNumber);
+      }
+    } finally {
+      writer.close();
+    }
+
+    return writer.toManifestFile();
+  }
+
+  private static MapPartitionsFunction<Row, ManifestFile> toManifests(
+      Broadcast<FileIO> io, long maxNumManifestEntries, String location,
+      int format, PartitionSpec spec, StructType sparkType) {
+
+    return (MapPartitionsFunction<Row, ManifestFile>) rows -> {
+      List<Row> rowsAsList = Lists.newArrayList(rows);
+
+      if (rowsAsList.isEmpty()) {

Review comment:
       It is on my TODO list for quite some time too. We also don't need to collect this into a list for unpartitioned tables. Maybe, if we could buffer the excess for some time before it gets too large so it deserves a separate file or if does not reach that threshold, we just write it to the existing file. We can probably write that using the iterator.




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