[GitHub] [iceberg] holdenk commented on a change in pull request #2272: Support structured streaming read for Iceberg

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

holdenk commented on a change in pull request #2272:
URL: https://github.com/apache/iceberg/pull/2272#discussion_r630407298



##########
File path: spark2/src/main/java/org/apache/iceberg/spark/source/StreamingReader.java
##########
@@ -0,0 +1,370 @@
+/*
+ * 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.util.Collections;
+import java.util.List;
+import java.util.Objects;
+import java.util.Optional;
+import java.util.stream.Collectors;
+import org.apache.commons.collections.CollectionUtils;
+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.Snapshot;
+import org.apache.iceberg.Table;
+import org.apache.iceberg.encryption.EncryptionManager;
+import org.apache.iceberg.io.CloseableIterable;
+import org.apache.iceberg.io.FileIO;
+import org.apache.iceberg.relocated.com.google.common.annotations.VisibleForTesting;
+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.SparkReadOptions;
+import org.apache.iceberg.util.Pair;
+import org.apache.iceberg.util.PropertyUtil;
+import org.apache.iceberg.util.SnapshotUtil;
+import org.apache.iceberg.util.TableScanUtil;
+import org.apache.spark.broadcast.Broadcast;
+import org.apache.spark.sql.sources.v2.DataSourceOptions;
+import org.apache.spark.sql.sources.v2.reader.streaming.MicroBatchReader;
+import org.apache.spark.sql.sources.v2.reader.streaming.Offset;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+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;
+
+/**
+ * A micro-batch based Spark Structured Streaming reader for Iceberg table. It will track the added
+ * files and generate tasks per batch to process newly added files. By default it will process
+ * all the newly added files to the current snapshot in each batch, user could also set this
+ * configuration "max-files-per-trigger" to control the number of files processed per batch.
+ */
+class StreamingReader extends Reader implements MicroBatchReader {
+  private static final Logger LOG = LoggerFactory.getLogger(StreamingReader.class);
+  private static final String MAX_SIZE_PER_BATCH = "max-size-per-batch";
+  private static final String START_SNAPSHOT_ID = "start-snapshot-id";
+
+  private StreamingOffset startOffset;
+  private StreamingOffset endOffset;
+
+  private final Table table;
+  private final long maxSizePerBatch;
+  private final Long startSnapshotId;
+  private final long splitSize;
+  private final int splitLookback;
+  private final long splitOpenFileCost;
+  private Boolean readUsingBatch = null;
+
+  /**
+   * Used to cache the pending batches for this streaming batch interval.
+   */
+  private Pair<StreamingOffset, List<MicroBatch>> cachedPendingBatches = null;
+
+  StreamingReader(Table table, Broadcast<FileIO> io, Broadcast<EncryptionManager> encryptionManager,
+      boolean caseSensitive, DataSourceOptions options) {
+    super(table, io, encryptionManager, caseSensitive, options);
+
+    this.table = table;
+    this.maxSizePerBatch = options.get(MAX_SIZE_PER_BATCH).map(Long::parseLong).orElse(Long.MAX_VALUE);
+    Preconditions.checkArgument(maxSizePerBatch > 0L,
+        "Option max-size-per-batch '%s' should > 0", maxSizePerBatch);
+
+    this.startSnapshotId = options.get(START_SNAPSHOT_ID).map(Long::parseLong).orElse(null);
+    if (startSnapshotId != null) {
+      if (!SnapshotUtil.ancestorOf(table, table.currentSnapshot().snapshotId(), startSnapshotId)) {
+        throw new IllegalArgumentException("The option start-snapshot-id " + startSnapshotId +
+            " is not an ancestor of the current snapshot");
+      }
+    }
+
+    long tableSplitSize = Optional.ofNullable(splitSize())
+        .orElseGet(
+            () -> PropertyUtil.propertyAsLong(table.properties(), SPLIT_SIZE, SPLIT_SIZE_DEFAULT));
+    int tableSplitLookback = Optional.ofNullable(splitLookback())
+        .orElseGet(() -> PropertyUtil
+            .propertyAsInt(table.properties(), SPLIT_LOOKBACK, SPLIT_LOOKBACK_DEFAULT));
+    long tableSplitOpenFileCost = Optional.ofNullable(splitOpenFileCost())
+        .orElseGet(() -> PropertyUtil.propertyAsLong(table.properties(), SPLIT_OPEN_FILE_COST,
+            SPLIT_OPEN_FILE_COST_DEFAULT));
+
+    this.splitSize = options.getLong(SparkReadOptions.SPLIT_SIZE, tableSplitSize);
+    this.splitLookback = options.getInt(SparkReadOptions.LOOKBACK, tableSplitLookback);
+    this.splitOpenFileCost = options
+        .getLong(SparkReadOptions.FILE_OPEN_COST, tableSplitOpenFileCost);
+  }
+
+  @Override
+  @SuppressWarnings("unchecked")
+  public void setOffsetRange(Optional<Offset> start, Optional<Offset> end) {
+    table.refresh();
+
+    if (start.isPresent() && !StreamingOffset.START_OFFSET.equals(start.get())) {
+      this.startOffset = (StreamingOffset) start.get();
+      this.endOffset = (StreamingOffset) end.orElseGet(() -> calculateEndOffset(startOffset));
+    } else {
+      // If starting offset is "START_OFFSET" (there's no snapshot in the last batch), or starting
+      // offset is not set, then we need to calculate the starting offset again.
+      this.startOffset = calculateStartingOffset();
+      this.endOffset = calculateEndOffset(startOffset);
+    }
+  }
+
+  @Override
+  public Offset getStartOffset() {
+    if (startOffset == null) {
+      throw new IllegalStateException("Start offset is not set");
+    }
+
+    return startOffset;
+  }
+
+  @Override
+  public Offset getEndOffset() {
+    if (endOffset == null) {
+      throw new IllegalStateException("End offset is not set");
+    }
+
+    return endOffset;
+  }
+
+  @Override
+  public Offset deserializeOffset(String json) {
+    return StreamingOffset.fromJson(json);
+  }
+
+  @Override
+  public void commit(Offset end) {

Review comment:
       Would it make sense to clean up the cachedPendingBatches here, or would they already have been removed at this point?

##########
File path: spark2/src/main/java/org/apache/iceberg/spark/source/IcebergSource.java
##########
@@ -127,6 +130,23 @@ public StreamWriter createStreamWriter(String runId, StructType dsStruct,
     return new StreamingWriter(table, io, encryptionManager, options, queryId, mode, appId, writeSchema, dsStruct);
   }
 
+  @Override
+  public MicroBatchReader createMicroBatchReader(Optional<StructType> schema, String checkpointLocation,

Review comment:
       So it seems like we're not using the checkpointLocation here, do we not need to store anything to be able to recover on failure? I think this is the case because as we read data it's not like it gets "consumed" but I just want to make sure.

##########
File path: spark2/src/main/java/org/apache/iceberg/spark/source/IcebergSource.java
##########
@@ -127,6 +130,23 @@ public StreamWriter createStreamWriter(String runId, StructType dsStruct,
     return new StreamingWriter(table, io, encryptionManager, options, queryId, mode, appId, writeSchema, dsStruct);
   }
 
+  @Override
+  public MicroBatchReader createMicroBatchReader(Optional<StructType> schema, String checkpointLocation,
+                                                 DataSourceOptions options) {
+    if (schema.isPresent()) {
+      throw new IllegalStateException("Iceberg does not support specifying the schema at read time");
+    }
+
+    Configuration conf = new Configuration(lazyBaseConf());
+    Table table = getTableAndResolveHadoopConfiguration(options, conf);
+    String caseSensitive = lazySparkSession().conf().get("spark.sql.caseSensitive");

Review comment:
       Maybe add a comment about why this is resolved from the session conf instead of the merged session conf / source options?




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