[Managed Iceberg] Fix partition value race condition (apache#33549)

* fix and update tests

* dont mention df yet

* add PR link

* whitespace

.github/trigger_files/IO_Iceberg_Integration_Tests.json

@@ -1,4 +1,4 @@
 {
-    "comment": "Modify this file in a trivial way to cause this test suite to run",
+    "comment": "Modify this file in a trivial way to cause this test suite to run.",
     "modification": 1
 }

CHANGES.md

@@ -115,6 +115,7 @@
 ## Bugfixes
 
 * Fixed EventTimeTimer ordering in Prism. ([#32222](https://github.com/apache/beam/issues/32222)).
+* [Managed Iceberg] Fixed a bug where DataFile metadata was assigned incorrect partition values ([#33549](https://github.com/apache/beam/pull/33549)).
 
 ## Security Fixes
 
@@ -157,6 +158,11 @@
 * Adding flag to support conditionally disabling auto-commit in JdbcIO ReadFn ([#31111](https://github.com/apache/beam/issues/31111))
 * (Python) Fixed BigQuery Enrichment bug that can lead to multiple conditions returning duplicate rows, batching returning incorrect results and conditions not scoped by row during batching ([#32780](https://github.com/apache/beam/pull/32780)).
 
+## Known Issues
+
+* [Managed Iceberg] DataFile metadata is assigned incorrect partition values ([#33497](https://github.com/apache/beam/issues/33497)).
+  * Fixed in 2.62.0
+
 # [2.60.0] - 2024-10-17
 
 ## Highlights
@@ -211,6 +217,8 @@ when running on 3.8. ([#31192](https://github.com/apache/beam/issues/31192))
   * Duplicate Rows: Multiple conditions may be applied incorrectly, leading to the duplication of rows in the output.
   * Incorrect Results with Batched Requests: Conditions may not be correctly scoped to individual rows within the batch, potentially causing inaccurate results.
   * Fixed in 2.61.0.
+* [Managed Iceberg] DataFile metadata is assigned incorrect partition values ([#33497](https://github.com/apache/beam/issues/33497)).
+  * Fixed in 2.62.0
 
 # [2.59.0] - 2024-09-11
 
@@ -259,6 +267,8 @@ when running on 3.8. ([#31192](https://github.com/apache/beam/issues/31192))
   * Duplicate Rows: Multiple conditions may be applied incorrectly, leading to the duplication of rows in the output.
   * Incorrect Results with Batched Requests: Conditions may not be correctly scoped to individual rows within the batch, potentially causing inaccurate results.
   * Fixed in 2.61.0.
+* [Managed Iceberg] DataFile metadata is assigned incorrect partition values ([#33497](https://github.com/apache/beam/issues/33497)).
+  * Fixed in 2.62.0
 
 # [2.58.1] - 2024-08-15
 

sdks/java/io/iceberg/src/main/java/org/apache/beam/sdk/io/iceberg/RecordWriterManager.java

@@ -96,7 +96,9 @@ class DestinationState {
     private final IcebergDestination icebergDestination;
     private final PartitionSpec spec;
     private final org.apache.iceberg.Schema schema;
-    private final PartitionKey partitionKey;
+    // used to determine the partition to which a record belongs
+    // must not be directly used to create a writer
+    private final PartitionKey routingPartitionKey;
     private final Table table;
     private final String stateToken = UUID.randomUUID().toString();
     final Cache<PartitionKey, RecordWriter> writers;
@@ -109,7 +111,7 @@ class DestinationState {
       this.icebergDestination = icebergDestination;
       this.schema = table.schema();
       this.spec = table.spec();
-      this.partitionKey = new PartitionKey(spec, schema);
+      this.routingPartitionKey = new PartitionKey(spec, schema);
       this.table = table;
       for (PartitionField partitionField : spec.fields()) {
         partitionFieldMap.put(partitionField.name(), partitionField);
@@ -154,12 +156,12 @@ class DestinationState {
      * can't create a new writer, the {@link Record} is rejected and {@code false} is returned.
      */
     boolean write(Record record) {
-      partitionKey.partition(getPartitionableRecord(record));
+      routingPartitionKey.partition(getPartitionableRecord(record));
 
-      if (!writers.asMap().containsKey(partitionKey) && openWriters >= maxNumWriters) {
+      if (!writers.asMap().containsKey(routingPartitionKey) && openWriters >= maxNumWriters) {
         return false;
       }
-      RecordWriter writer = fetchWriterForPartition(partitionKey);
+      RecordWriter writer = fetchWriterForPartition(routingPartitionKey);
       writer.write(record);
       return true;
     }
@@ -173,10 +175,12 @@ private RecordWriter fetchWriterForPartition(PartitionKey partitionKey) {
       RecordWriter recordWriter = writers.getIfPresent(partitionKey);
 
       if (recordWriter == null || recordWriter.bytesWritten() > maxFileSize) {
+        // each writer must have its own PartitionKey object
+        PartitionKey copy = partitionKey.copy();
         // calling invalidate for a non-existent key is a safe operation
-        writers.invalidate(partitionKey);
-        recordWriter = createWriter(partitionKey);
-        writers.put(partitionKey, recordWriter);
+        writers.invalidate(copy);
+        recordWriter = createWriter(copy);
+        writers.put(copy, recordWriter);
       }
       return recordWriter;
     }

sdks/java/io/iceberg/src/test/java/org/apache/beam/sdk/io/iceberg/catalog/IcebergCatalogBaseIT.java

@@ -28,10 +28,13 @@
 import java.io.Serializable;
 import java.util.ArrayList;
 import java.util.Arrays;
+import java.util.Collections;
 import java.util.HashMap;
 import java.util.List;
 import java.util.Map;
+import java.util.Set;
 import java.util.UUID;
+import java.util.function.BiFunction;
 import java.util.stream.Collectors;
 import java.util.stream.LongStream;
 import java.util.stream.Stream;
@@ -65,6 +68,7 @@
 import org.apache.iceberg.TableScan;
 import org.apache.iceberg.catalog.Catalog;
 import org.apache.iceberg.catalog.TableIdentifier;
+import org.apache.iceberg.data.IdentityPartitionConverters;
 import org.apache.iceberg.data.Record;
 import org.apache.iceberg.data.parquet.GenericParquetReaders;
 import org.apache.iceberg.data.parquet.GenericParquetWriter;
@@ -74,7 +78,10 @@
 import org.apache.iceberg.io.InputFile;
 import org.apache.iceberg.io.OutputFile;
 import org.apache.iceberg.parquet.Parquet;
+import org.apache.iceberg.types.Type;
+import org.apache.iceberg.types.TypeUtil;
 import org.apache.iceberg.util.DateTimeUtil;
+import org.apache.iceberg.util.PartitionUtil;
 import org.checkerframework.checker.nullness.qual.Nullable;
 import org.joda.time.DateTime;
 import org.joda.time.DateTimeZone;
@@ -295,6 +302,22 @@ private List<Row> populateTable(Table table) throws IOException {
     return expectedRows;
   }
 
+  private static Map<Integer, ?> constantsMap(
+      FileScanTask task,
+      BiFunction<Type, Object, Object> converter,
+      org.apache.iceberg.Schema schema) {
+    PartitionSpec spec = task.spec();
+    Set<Integer> idColumns = spec.identitySourceIds();
+    org.apache.iceberg.Schema partitionSchema = TypeUtil.select(schema, idColumns);
+    boolean projectsIdentityPartitionColumns = !partitionSchema.columns().isEmpty();
+
+    if (projectsIdentityPartitionColumns) {
+      return PartitionUtil.constantsMap(task, converter);
+    } else {
+      return Collections.emptyMap();
+    }
+  }
+
   private List<Record> readRecords(Table table) {
     org.apache.iceberg.Schema tableSchema = table.schema();
     TableScan tableScan = table.newScan().project(tableSchema);
@@ -303,13 +326,16 @@ private List<Record> readRecords(Table table) {
       InputFilesDecryptor descryptor =
           new InputFilesDecryptor(task, table.io(), table.encryption());
       for (FileScanTask fileTask : task.files()) {
+        Map<Integer, ?> idToConstants =
+            constantsMap(fileTask, IdentityPartitionConverters::convertConstant, tableSchema);
         InputFile inputFile = descryptor.getInputFile(fileTask);
         CloseableIterable<Record> iterable =
             Parquet.read(inputFile)
                 .split(fileTask.start(), fileTask.length())
                 .project(tableSchema)
                 .createReaderFunc(
-                    fileSchema -> GenericParquetReaders.buildReader(tableSchema, fileSchema))
+                    fileSchema ->
+                        GenericParquetReaders.buildReader(tableSchema, fileSchema, idToConstants))
                 .filter(fileTask.residual())
                 .build();