[GitHub] [iceberg] jackye1995 commented on a change in pull request #2660: Spark3 structured streaming micro_batch read support

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

jackye1995 commented on a change in pull request #2660:
URL: https://github.com/apache/iceberg/pull/2660#discussion_r648727081



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File path: spark3/src/main/java/org/apache/iceberg/spark/source/SparkMicroBatchStream.java
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@@ -0,0 +1,306 @@
+/*
+ * 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.source;
+
+import java.io.BufferedWriter;
+import java.io.IOException;
+import java.io.InputStream;
+import java.io.OutputStream;
+import java.io.OutputStreamWriter;
+import java.nio.charset.StandardCharsets;
+import java.util.ArrayList;
+import java.util.List;
+import java.util.Optional;
+import org.apache.iceberg.CombinedScanTask;
+import org.apache.iceberg.DataOperations;
+import org.apache.iceberg.FileScanTask;
+import org.apache.iceberg.MicroBatches;
+import org.apache.iceberg.MicroBatches.MicroBatch;
+import org.apache.iceberg.Schema;
+import org.apache.iceberg.SchemaParser;
+import org.apache.iceberg.SerializableTable;
+import org.apache.iceberg.Snapshot;
+import org.apache.iceberg.Table;
+import org.apache.iceberg.io.CloseableIterable;
+import org.apache.iceberg.relocated.com.google.common.base.Preconditions;
+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.Spark3Util;
+import org.apache.iceberg.spark.SparkReadOptions;
+import org.apache.iceberg.spark.source.SparkBatchScan.ReadTask;
+import org.apache.iceberg.spark.source.SparkBatchScan.ReaderFactory;
+import org.apache.iceberg.util.PropertyUtil;
+import org.apache.iceberg.util.SnapshotUtil;
+import org.apache.iceberg.util.TableScanUtil;
+import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.broadcast.Broadcast;
+import org.apache.spark.sql.SparkSession;
+import org.apache.spark.sql.connector.read.InputPartition;
+import org.apache.spark.sql.connector.read.PartitionReaderFactory;
+import org.apache.spark.sql.connector.read.streaming.MicroBatchStream;
+import org.apache.spark.sql.connector.read.streaming.Offset;
+import org.apache.spark.sql.execution.streaming.HDFSMetadataLog;
+import org.apache.spark.sql.util.CaseInsensitiveStringMap;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import scala.reflect.ClassTag;
+
+import static org.apache.iceberg.TableProperties.SPLIT_LOOKBACK;
+import static org.apache.iceberg.TableProperties.SPLIT_LOOKBACK_DEFAULT;
+import static org.apache.iceberg.TableProperties.SPLIT_OPEN_FILE_COST;
+import static org.apache.iceberg.TableProperties.SPLIT_OPEN_FILE_COST_DEFAULT;
+import static org.apache.iceberg.TableProperties.SPLIT_SIZE;
+import static org.apache.iceberg.TableProperties.SPLIT_SIZE_DEFAULT;
+
+public class SparkMicroBatchStream implements MicroBatchStream {
+  private static final Logger LOG = LoggerFactory.getLogger(SparkMicroBatchStream.class);
+
+  private final JavaSparkContext sparkContext;
+  private final Table table;
+  private final boolean caseSensitive;
+  private final Schema expectedSchema;
+  private final Long splitSize;
+  private final Integer splitLookback;
+  private final Long splitOpenFileCost;
+  private final boolean localityPreferred;
+  private final OffsetLog offsetLog;
+
+  private StreamingOffset initialOffset = null;
+
+  SparkMicroBatchStream(SparkSession spark, JavaSparkContext sparkContext,
+                        Table table, boolean caseSensitive, Schema expectedSchema,
+                        CaseInsensitiveStringMap options, String checkpointLocation) {
+    this.sparkContext = sparkContext;
+    this.table = table;
+    this.caseSensitive = caseSensitive;
+    this.expectedSchema = expectedSchema;
+    this.localityPreferred = Spark3Util.isLocalityEnabled(table.io(), table.location(), options);
+    this.splitSize = Optional.ofNullable(Spark3Util.propertyAsLong(options, SparkReadOptions.SPLIT_SIZE, null))
+        .orElseGet(() -> PropertyUtil.propertyAsLong(table.properties(), SPLIT_SIZE, SPLIT_SIZE_DEFAULT));
+    this.splitLookback = Optional.ofNullable(Spark3Util.propertyAsInt(options, SparkReadOptions.LOOKBACK, null))
+        .orElseGet(() -> PropertyUtil.propertyAsInt(table.properties(), SPLIT_LOOKBACK, SPLIT_LOOKBACK_DEFAULT));
+    this.splitOpenFileCost = Optional.ofNullable(
+        Spark3Util.propertyAsLong(options, SparkReadOptions.FILE_OPEN_COST, null))
+        .orElseGet(() -> PropertyUtil.propertyAsLong(table.properties(), SPLIT_OPEN_FILE_COST,
+            SPLIT_OPEN_FILE_COST_DEFAULT));
+    this.offsetLog = OffsetLog.getInstance(spark, checkpointLocation);
+  }
+
+  @Override
+  public Offset latestOffset() {
+    initialOffset();
+
+    Snapshot latestSnapshot = table.currentSnapshot();
+    if (latestSnapshot == null) {
+      return StreamingOffset.START_OFFSET;
+    }
+
+    return new StreamingOffset(
+        latestSnapshot.snapshotId(),
+        Iterables.size(latestSnapshot.addedFiles()),
+        latestSnapshot.snapshotId() == initialOffset.snapshotId());
+  }
+
+  @Override
+  public InputPartition[] planInputPartitions(Offset start, Offset end) {
+    if (end.equals(StreamingOffset.START_OFFSET)) {
+      return new InputPartition[0];
+    }
+
+    // broadcast the table metadata as input partitions will be sent to executors
+    Broadcast<Table> tableBroadcast = sparkContext.broadcast(SerializableTable.copyOf(table));
+    String expectedSchemaString = SchemaParser.toJson(expectedSchema);
+
+    Preconditions.checkState(
+        end instanceof StreamingOffset,
+        "The end offset passed to planInputPartitions() is not an instance of StreamingOffset.");
+
+    Preconditions.checkState(
+        start instanceof StreamingOffset,
+        "The start offset passed to planInputPartitions() is not an instance of StreamingOffset.");
+
+    StreamingOffset endOffset = (StreamingOffset) end;
+    StreamingOffset startOffset = (StreamingOffset) start;
+
+    List<FileScanTask> fileScanTasks = getFileScanTasks(startOffset, endOffset);
+
+    CloseableIterable<FileScanTask> splitTasks = TableScanUtil.splitFiles(
+        CloseableIterable.withNoopClose(fileScanTasks),
+        splitSize);
+    List<CombinedScanTask> combinedScanTasks = Lists.newArrayList(
+        TableScanUtil.planTasks(splitTasks, splitSize, splitLookback, splitOpenFileCost));
+    InputPartition[] readTasks = new InputPartition[combinedScanTasks.size()];
+
+    for (int i = 0; i < combinedScanTasks.size(); i++) {
+      readTasks[i] = new ReadTask(
+          combinedScanTasks.get(i), tableBroadcast, expectedSchemaString,
+          caseSensitive, localityPreferred);
+    }
+
+    return readTasks;
+  }
+
+  @Override
+  public PartitionReaderFactory createReaderFactory() {
+    int batchSizeValueToDisableColumnarReads = 0;
+    return new ReaderFactory(batchSizeValueToDisableColumnarReads);
+  }
+
+  @Override
+  public Offset initialOffset() {
+    if (initialOffset != null) {
+      return initialOffset;
+    }
+
+    if (offsetLog.isOffsetLogInitialized()) {
+      initialOffset = offsetLog.getLatest();
+      return initialOffset;
+    }
+
+    if (table.currentSnapshot() == null) {
+      initialOffset = StreamingOffset.START_OFFSET;
+    } else {
+      initialOffset = new StreamingOffset(
+          SnapshotUtil.oldestSnapshot(table).snapshotId(), 0, true);
+      this.offsetLog.addInitialOffset(initialOffset);
+    }
+
+    return initialOffset;
+  }
+
+  @Override
+  public Offset deserializeOffset(String json) {
+    return StreamingOffset.fromJson(json);
+  }
+
+  @Override
+  public void commit(Offset end) {
+  }
+
+  @Override
+  public void stop() {
+  }
+
+  private List<FileScanTask> getFileScanTasks(StreamingOffset startOffset, StreamingOffset endOffset) {
+    List<FileScanTask> fileScanTasks = new ArrayList<>();
+    MicroBatch latestMicroBatch = null;
+    do {
+      final StreamingOffset currentOffset =
+          latestMicroBatch != null && latestMicroBatch.lastIndexOfSnapshot() ?
+          getNextAvailableSnapshot(latestMicroBatch.snapshotId()) :
+          startOffset;
+
+      latestMicroBatch = MicroBatches.from(table.snapshot(currentOffset.snapshotId()), table.io())
+          .caseSensitive(caseSensitive)
+          .specsById(table.specs())
+          .generate(currentOffset.position(), Long.MAX_VALUE, currentOffset.shouldScanAllFiles());
+
+      fileScanTasks.addAll(latestMicroBatch.tasks());
+    } while (latestMicroBatch.snapshotId() != endOffset.snapshotId());
+
+    return fileScanTasks;
+  }
+
+  private StreamingOffset getNextAvailableSnapshot(long snapshotId) {
+    Snapshot previousSnapshot = table.snapshot(snapshotId);
+    Snapshot pointer = table.currentSnapshot();
+    while (pointer != null && previousSnapshot.snapshotId() != pointer.parentId()) {
+      Preconditions.checkState(pointer.operation().equals(DataOperations.APPEND),
+          "Encountered Snapshot DataOperation other than APPEND.");
+
+      pointer = table.snapshot(pointer.parentId());
+    }
+
+    Preconditions.checkState(pointer != null,
+        "snapshot on which the stream operated has been garbage collected.");
+
+    return new StreamingOffset(pointer.snapshotId(), 0L, false);
+  }
+
+  interface OffsetLog {
+    static OffsetLog getInstance(SparkSession spark, String checkpointLocation) {
+      return new OffsetLogImpl(spark, checkpointLocation);
+    }
+
+    void addInitialOffset(StreamingOffset offset);
+
+    boolean isOffsetLogInitialized();
+
+    StreamingOffset getLatest();
+  }
+
+  private static class OffsetLogImpl implements OffsetLog {
+    private final IcebergSourceOffsetLog offsetSeqLog;
+
+    OffsetLogImpl(SparkSession spark, String checkpointLocation) {
+      this.offsetSeqLog = checkpointLocation != null ?
+          new IcebergSourceOffsetLog(spark, checkpointLocation) :
+          null;
+    }
+
+    @Override
+    public void addInitialOffset(StreamingOffset offset) {
+      this.offsetSeqLog.add(0, offset);
+    }
+
+    @Override
+    public boolean isOffsetLogInitialized() {
+      return offsetSeqLog != null &&
+          offsetSeqLog.getLatest() != null &&
+          offsetSeqLog.getLatest().isDefined();
+    }
+
+    @Override
+    public StreamingOffset getLatest() {
+      return offsetSeqLog.getLatest().get()._2;
+    }
+  }
+
+  private static class IcebergSourceOffsetLog extends HDFSMetadataLog<StreamingOffset> {

Review comment:
       Yes S3 is now strongly consistent in listing and read-after-write, so that warning message is out of date.
   
   For the point that Russell pointed out, I remember we had a discussion in the last sync meeting about if we would like to have 1 runtime for 1 Spark minor release. I don't recall we arrived at a conclusion on that. If we decide to go with that approach, then this method is fine.
   
   If we do not go with that approach, then it is probably gonna be a trouble in the future. Because S3 is not a concern anymore, we can directly write the file through HDFS file system API, or even better the Iceberg FileIO API. But that will be a bit of duplication with the Spark codebase and some more effort in this PR. 




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