[lake/paimon] Support NestedRow types for tiering paimon #2260
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| Original file line number | Diff line number | Diff line change |
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@@ -489,6 +489,93 @@ private String getPartitionOffsetStr(Map<Long, String> partitionNameByIds) { | |
| return "[" + String.join(",", partitionOffsetStrs) + "]"; | ||
| } | ||
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| private static Stream<Arguments> tieringNestedRowWriteArgs() { | ||
| return Stream.of(Arguments.of(true), Arguments.of(false)); | ||
| } | ||
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| @ParameterizedTest | ||
| @MethodSource("tieringNestedRowWriteArgs") | ||
| void testTieringForNestedRow(boolean isPrimaryKeyTable) throws Exception { | ||
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Member
There was a problem hiding this comment. The IT cases are already quite heavy. This PR adds two new IT cases, but we should avoid introducing additional ones if we can reuse existing tests instead. In particular, it would be more efficient to add the new row-based test scenarios directly into For reference, see how this was done in: #2166.
Contributor
Author
There was a problem hiding this comment.
Okay, I'll make the changes. |
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| TablePath t1 = | ||
| TablePath.of( | ||
| DEFAULT_DB, | ||
| isPrimaryKeyTable ? "pkTableForNestedRow" : "logTableForNestedRow"); | ||
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| Schema.Builder builder = | ||
| Schema.newBuilder() | ||
| .column("c0", DataTypes.INT()) | ||
| .column("c1", DataTypes.STRING()) | ||
| .column( | ||
| "c2", | ||
| DataTypes.ROW( | ||
| DataTypes.FIELD("nested_int", DataTypes.INT()), | ||
| DataTypes.FIELD("nested_string", DataTypes.STRING()), | ||
| DataTypes.FIELD("nested_double", DataTypes.DOUBLE()))); | ||
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| if (isPrimaryKeyTable) { | ||
| builder.primaryKey("c0", "c1"); | ||
| } | ||
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| TableDescriptor.Builder tableDescriptor = | ||
| TableDescriptor.builder() | ||
| .schema(builder.build()) | ||
| .distributedBy(1, "c0") | ||
| .property(ConfigOptions.TABLE_DATALAKE_ENABLED.key(), "true") | ||
| .property(ConfigOptions.TABLE_DATALAKE_FRESHNESS, Duration.ofMillis(500)); | ||
| tableDescriptor.customProperties(Collections.emptyMap()); | ||
| tableDescriptor.properties(Collections.emptyMap()); | ||
| long t1Id = createTable(t1, tableDescriptor.build()); | ||
| TableBucket t1Bucket = new TableBucket(t1Id, 0); | ||
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| List<InternalRow> rows = | ||
| Collections.singletonList( | ||
| row( | ||
| builder.build().getRowType(), | ||
| 1, | ||
| "outer_value", | ||
| new Object[] {100, "nested_value", 3.14})); | ||
| writeRows(t1, rows, !isPrimaryKeyTable); | ||
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| if (isPrimaryKeyTable) { | ||
| waitUntilSnapshot(t1Id, 1, 0); | ||
| } | ||
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| JobClient jobClient = buildTieringJob(execEnv); | ||
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| try { | ||
| assertReplicaStatus(t1Bucket, 1); | ||
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| Iterator<org.apache.paimon.data.InternalRow> paimonRowIterator = | ||
| getPaimonRowCloseableIterator(t1); | ||
| for (InternalRow expectedRow : rows) { | ||
| org.apache.paimon.data.InternalRow row = paimonRowIterator.next(); | ||
| assertThat(row.getInt(0)).isEqualTo(expectedRow.getInt(0)); | ||
| assertThat(row.getString(1).toString()) | ||
| .isEqualTo(expectedRow.getString(1).toString()); | ||
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| org.apache.paimon.data.InternalRow paimonNestedRow = row.getRow(2, 3); | ||
| assertThat(paimonNestedRow).isNotNull(); | ||
| org.apache.fluss.row.InternalRow flussNestedRow = expectedRow.getRow(2, 3); | ||
| assertThat(paimonNestedRow.getInt(0)).isEqualTo(flussNestedRow.getInt(0)); | ||
| assertThat(paimonNestedRow.getString(1).toString()) | ||
| .isEqualTo(flussNestedRow.getString(1).toString()); | ||
| assertThat(paimonNestedRow.getDouble(2)).isEqualTo(flussNestedRow.getDouble(2)); | ||
| } | ||
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| Map<String, String> properties = | ||
| new HashMap<String, String>() { | ||
| { | ||
| put( | ||
| FLUSS_LAKE_SNAP_BUCKET_OFFSET_PROPERTY, | ||
| "[{\"bucket\":0,\"offset\":1}]"); | ||
| } | ||
| }; | ||
| checkSnapshotPropertyInPaimon(t1, properties); | ||
| } finally { | ||
| jobClient.cancel().get(); | ||
| } | ||
| } | ||
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| @Test | ||
| void testTieringToDvEnabledTable() throws Exception { | ||
| TablePath t1 = TablePath.of(DEFAULT_DB, "pkTableWithDv"); | ||
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Replace by
@ValueSource(booleans = {true, false})and removetieringNestedRowWriteArgsmethod.