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[HUDI-5585][flink]Fix flink creates and writes the table, the spark alter table reports an error #7706

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Merged
danny0405 merged 2 commits into from
Feb 1, 2023
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[HUDI-5585][flink]Fix flink creates and writes the table, the spark alter table reports an error #7706

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[HUDI-5585][flink]Fix flink creates and writes the table, the spark a…
Jan 19, 2023
8c4ddec
HUDI-5585
Jan 31, 2023
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8 changes: 5 additions & 3 deletions ...nk-datasource/hudi-flink/src/main/java/org/apache/hudi/table/catalog/HiveSchemaUtils.java
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Original file line number Diff line number Diff line change
Expand Up @@ -181,9 +181,11 @@ private static DataType toFlinkPrimitiveType(PrimitiveTypeInfo hiveType) {
*/
public static List<FieldSchema> toHiveFieldSchema(TableSchema schema, boolean withOperationField) {
List<FieldSchema> columns = new ArrayList<>();
Collection<String> metaFields = withOperationField
? HoodieRecord.HOODIE_META_COLUMNS_WITH_OPERATION // caution that the set may break sequence
: HoodieRecord.HOODIE_META_COLUMNS;
Collection<String> metaFields = new ArrayList<>(HoodieRecord.HOODIE_META_COLUMNS);
if (withOperationField) {
metaFields.add(HoodieRecord.OPERATION_METADATA_FIELD);
}

for (String metaField : metaFields) {
columns.add(new FieldSchema(metaField, "string", null));
}
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7 changes: 5 additions & 2 deletions ...-datasource/hudi-flink/src/main/java/org/apache/hudi/table/catalog/HoodieHiveCatalog.java
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Expand Up @@ -21,6 +21,7 @@
import org.apache.hudi.client.HoodieFlinkWriteClient;
import org.apache.hudi.common.fs.FSUtils;
import org.apache.hudi.common.model.HoodieFileFormat;
import org.apache.hudi.common.model.HoodieRecord;
import org.apache.hudi.common.table.HoodieTableConfig;
import org.apache.hudi.common.table.HoodieTableMetaClient;
import org.apache.hudi.common.table.timeline.HoodieActiveTimeline;
Expand Down Expand Up @@ -438,8 +439,10 @@ public CatalogBaseTable getTable(ObjectPath tablePath) throws TableNotExistExcep
LOG.warn("{} does not have any hoodie schema, and use hive table schema to infer the table schema", tablePath);
schema = HiveSchemaUtils.convertTableSchema(hiveTable);
}
org.apache.flink.table.api.Schema resultSchema = DataTypeUtils.dropIfExistsColumns(schema, HoodieRecord.HOODIE_META_COLUMNS_WITH_OPERATION);

@danny0405 danny0405 Jan 31, 2023

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In line419, we already ignore the metadata column, so why drop it again?

@waywtdcc waywtdcc Jan 31, 2023

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Indeed, I have removed.

Map<String, String> options = supplementOptions(tablePath, parameters);
return CatalogTable.of(schema, parameters.get(COMMENT),
return CatalogTable.of(resultSchema, parameters.get(COMMENT),
HiveSchemaUtils.getFieldNames(hiveTable.getPartitionKeys()), options);
}

Expand Down Expand Up @@ -819,7 +822,7 @@ public void dropPartition(
try (HoodieFlinkWriteClient<?> writeClient = createWriteClient(tablePath, table)) {
boolean hiveStylePartitioning = Boolean.parseBoolean(table.getOptions().get(FlinkOptions.HIVE_STYLE_PARTITIONING.key()));
writeClient.deletePartitions(
Collections.singletonList(HoodieCatalogUtil.inferPartitionPath(hiveStylePartitioning, partitionSpec)),
Collections.singletonList(HoodieCatalogUtil.inferPartitionPath(hiveStylePartitioning, partitionSpec)),
HoodieActiveTimeline.createNewInstantTime())
.forEach(writeStatus -> {
if (writeStatus.hasErrors()) {
Expand Down
24 changes: 23 additions & 1 deletion ...asource/hudi-flink/src/main/java/org/apache/hudi/table/catalog/TableOptionProperties.java
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Expand Up @@ -19,6 +19,7 @@
package org.apache.hudi.table.catalog;

import org.apache.hudi.common.fs.FSUtils;
import org.apache.hudi.common.model.HoodieRecord;
import org.apache.hudi.common.model.HoodieTableType;
import org.apache.hudi.common.table.TableSchemaResolver;
import org.apache.hudi.configuration.FlinkOptions;
Expand All @@ -28,6 +29,8 @@

import org.apache.avro.Schema;
import org.apache.flink.table.catalog.CatalogTable;
import org.apache.flink.table.types.logical.RowType;
import org.apache.flink.table.types.logical.VarCharType;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FSDataInputStream;
import org.apache.hadoop.fs.FSDataOutputStream;
Expand All @@ -39,7 +42,9 @@
import org.slf4j.LoggerFactory;

import java.io.IOException;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Collection;
import java.util.Collections;
import java.util.Date;
import java.util.HashMap;
Expand All @@ -49,6 +54,7 @@
import java.util.stream.Collectors;

import static org.apache.flink.table.factories.FactoryUtil.CONNECTOR;
import static org.apache.hudi.common.model.HoodieRecord.OPERATION_METADATA_FIELD;
import static org.apache.hudi.common.table.HoodieTableMetaClient.AUXILIARYFOLDER_NAME;

/**
Expand Down Expand Up @@ -169,7 +175,8 @@ public static Map<String, String> translateFlinkTableProperties2Spark(
Configuration hadoopConf,
Map<String, String> properties,
List<String> partitionKeys) {
Schema schema = AvroSchemaConverter.convertToSchema(catalogTable.getSchema().toPhysicalRowDataType().getLogicalType());
RowType containMetaFields = getContainMetaFields(catalogTable);
Schema schema = AvroSchemaConverter.convertToSchema(containMetaFields);
MessageType messageType = TableSchemaResolver.convertAvroSchemaToParquet(schema, hadoopConf);
String sparkVersion = catalogTable.getOptions().getOrDefault(SPARK_VERSION, DEFAULT_SPARK_VERSION);
Map<String, String> sparkTableProperties = SparkDataSourceTableUtils.getSparkTableProperties(
Expand All @@ -184,6 +191,21 @@ public static Map<String, String> translateFlinkTableProperties2Spark(
e -> e.getKey().equalsIgnoreCase(FlinkOptions.TABLE_TYPE.key()) ? VALUE_MAPPING.get(e.getValue()) : e.getValue()));
}

private static RowType getContainMetaFields(CatalogTable catalogTable) {
RowType rowType = (RowType) catalogTable.getSchema().toPhysicalRowDataType().getLogicalType().copy();
boolean withOperationField = Boolean.parseBoolean(catalogTable.getOptions().getOrDefault(FlinkOptions.CHANGELOG_ENABLED.key(), "false"));
Collection<String> metaFields = new ArrayList<>(HoodieRecord.HOODIE_META_COLUMNS);
if (withOperationField) {
metaFields.add(OPERATION_METADATA_FIELD);
}
ArrayList<RowType.RowField> rowFields = new ArrayList<>();
for (String metaField : metaFields) {
rowFields.add(new RowType.RowField(metaField, new VarCharType(10000)));
}
rowFields.addAll(rowType.getFields());
return new RowType(false, rowFields);
}

public static Map<String, String> translateSparkTableProperties2Flink(Map<String, String> options) {
if (options.containsKey(CONNECTOR.key())) {
return options;
Expand Down
24 changes: 24 additions & 0 deletions hudi-flink-datasource/hudi-flink/src/main/java/org/apache/hudi/util/DataTypeUtils.java
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Expand Up @@ -34,6 +34,7 @@
import java.time.LocalDateTime;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Collection;
import java.util.List;

/**
Expand Down Expand Up @@ -167,4 +168,27 @@ public static DataType ensureColumnsAsNonNullable(DataType dataType, @Nullable L
return DataTypes.ROW(fields.stream().toArray(DataTypes.Field[]::new)).notNull();
}

/**
* drop some columns.
*
* @param schema
* @param dropCols
* @return
*/
public static org.apache.flink.table.api.Schema dropIfExistsColumns(org.apache.flink.table.api.Schema schema, Collection<String> dropCols) {
ArrayList<org.apache.flink.table.api.Schema.UnresolvedColumn> unresolvedColumns = new ArrayList<>(schema.getColumns());
unresolvedColumns.removeIf(c -> dropCols.contains(c.getName()));
org.apache.flink.table.api.Schema.Builder builder =
org.apache.flink.table.api.Schema.newBuilder()
.fromColumns(unresolvedColumns);
if (schema.getPrimaryKey().isPresent()) {
builder.primaryKey(schema.getPrimaryKey().get().getColumnNames());
}
if (schema.getWatermarkSpecs() != null) {
schema.getWatermarkSpecs().forEach(w -> builder.watermark(w.getColumnName(), w.getWatermarkExpression()));
}
org.apache.flink.table.api.Schema resultSchema = builder.build();
return resultSchema;
}

}
6 changes: 5 additions & 1 deletion ...asource/hudi-flink/src/test/java/org/apache/hudi/table/catalog/TestHoodieHiveCatalog.java
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Expand Up @@ -138,7 +138,11 @@ public void testCreateAndGetHoodieTable(HoodieTableType tableType) throws Except
.map(f -> f.getName() + ":" + f.getType())
.collect(Collectors.joining(","));
assertEquals("par1:string", partitionSchema);

String avroSchemaStr = hiveTable.getParameters().get("spark.sql.sources.schema.part.0");
String expectAvroSchemaStr =
"{\"type\":\"struct\",\"fields\":[{\"name\":\"_hoodie_commit_time\",\"type\":\"string\",\"nullable\":true,\"metadata\":{}},{\"name\":\"_hoodie_commit_seqno\",\"type\":\"string\",\"nullable\":true,\"metadata\":{}},{\"name\":\"_hoodie_record_key\",\"type\":\"string\",\"nullable\":true,\"metadata\":{}},{\"name\":\"_hoodie_partition_path\",\"type\":\"string\",\"nullable\":true,\"metadata\":{}},{\"name\":\"_hoodie_file_name\",\"type\":\"string\",\"nullable\":true,\"metadata\":{}},{\"name\":\"uuid\",\"type\":\"integer\",\"nullable\":false,\"metadata\":{}},{\"name\":\"name\",\"type\":\"string\",\"nullable\":true,\"metadata\":{}},{\"name\":\"age\",\"type\":\"integer\",\"nullable\":true,\"metadata\":{}},{\"name\":\"ts\",\"type\":\"long\",\"nullable\":true,\"metadata\":{}},{\"name\":\"par1\",\"type\":\"string\",\"nullable\":true,\"metadata\":{}}]}";
assertEquals(avroSchemaStr, expectAvroSchemaStr);

// validate catalog table
CatalogBaseTable table1 = hoodieCatalog.getTable(tablePath);
assertEquals("hudi", table1.getOptions().get(CONNECTOR.key()));
Expand Down