shubham19may commented on code in PR #14499:
URL: https://github.com/apache/iceberg/pull/14499#discussion_r2498351892
##########
arrow/src/main/java/org/apache/iceberg/arrow/ArrowAllocation.java:
##########
@@ -21,14 +21,29 @@
import org.apache.arrow.memory.RootAllocator;
public class ArrowAllocation {
+ private static final String ALLOCATION_MANAGER_TYPE_PROPERTY =
+ "arrow.memory.allocation.manager.type";
+
static {
- ROOT_ALLOCATOR = new RootAllocator(Long.MAX_VALUE);
+ if (System.getProperty(ALLOCATION_MANAGER_TYPE_PROPERTY) == null) {
+ System.setProperty(ALLOCATION_MANAGER_TYPE_PROPERTY, "Netty");
+ }
Review Comment:
Done.
##########
spark/v4.0/spark/src/test/java/org/apache/iceberg/spark/data/TestSparkParquetReader.java:
##########
@@ -227,6 +228,69 @@ protected WriteSupport<InternalRow>
getWriteSupport(Configuration configuration)
}
}
+ @Test
+ public void testTimestampMillisProducedBySparkIsReadCorrectly() throws
IOException {
+ String outputFilePath =
+ String.format("%s/%s", temp.toAbsolutePath(),
"parquet_timestamp_millis.parquet");
+ HadoopOutputFile outputFile =
+ HadoopOutputFile.fromPath(
+ new org.apache.hadoop.fs.Path(outputFilePath), new
Configuration());
+
+ Schema schema = new Schema(required(1, "event_time",
Types.TimestampType.withZone()));
+
+ StructType sparkSchema =
+ new StructType(
+ new StructField[] {
+ new StructField("event_time", DataTypes.TimestampType, false,
Metadata.empty())
+ });
+
+ List<InternalRow> originalRows =
Lists.newArrayList(RandomData.generateSpark(schema, 10, 0L));
+ List<InternalRow> rows = Lists.newArrayList();
+ for (InternalRow row : originalRows) {
+ long timestampMicros = row.getLong(0);
+ long timestampMillis = (timestampMicros / 1000) * 1000;
+ rows.add(
+ new org.apache.spark.sql.catalyst.expressions.GenericInternalRow(
+ new Object[] {timestampMillis}));
+ }
+
+ try (ParquetWriter<InternalRow> writer =
+ new NativeSparkWriterBuilder(outputFile)
+ .set("org.apache.spark.sql.parquet.row.attributes",
sparkSchema.json())
+ .set("spark.sql.parquet.writeLegacyFormat", "false")
+ .set("spark.sql.parquet.outputTimestampType", "TIMESTAMP_MILLIS")
+ .set("spark.sql.parquet.fieldId.write.enabled", "true")
+ .build()) {
+ for (InternalRow row : rows) {
+ writer.write(row);
+ }
+ }
+
+ InputFile parquetInputFile = Files.localInput(outputFilePath);
+ Table timestampMillisTable = tableFromInputFile(parquetInputFile, schema);
+
+ int totalRowsRead = 0;
+ try (VectorizedTableScanIterable vectorizedReader =
+ new VectorizedTableScanIterable(timestampMillisTable.newScan(), 1024,
false)) {
+
+ for (org.apache.iceberg.arrow.vectorized.ColumnarBatch batch :
vectorizedReader) {
+ org.apache.arrow.vector.VectorSchemaRoot root =
batch.createVectorSchemaRootFromVectors();
+
+ org.apache.arrow.vector.FieldVector eventTimeVector =
root.getVector("event_time");
+ assertThat(eventTimeVector).isNotNull();
+
assertThat(eventTimeVector).isInstanceOf(org.apache.arrow.vector.BigIntVector.class);
Review Comment:
done.
also, in VectorizedParquetDefinitionLevelReader.java, arrow validity buffer
was not being properly set for non-null values. (bit should be 1 when Value is
not null). Fixed that.
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