hililiwei commented on code in PR #4904: URL: https://github.com/apache/iceberg/pull/4904#discussion_r910559643
########## flink/v1.15/flink/src/main/java/org/apache/iceberg/flink/sink/v2/FlinkSink.java: ########## @@ -0,0 +1,635 @@ +/* + * 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.flink.sink.v2; + +import java.io.IOException; +import java.io.UncheckedIOException; +import java.util.Collection; +import java.util.List; +import java.util.Locale; +import java.util.Map; +import java.util.Set; +import java.util.function.Function; +import javax.annotation.Nullable; +import org.apache.flink.api.common.functions.MapFunction; +import org.apache.flink.api.common.functions.RichMapFunction; +import org.apache.flink.api.common.typeinfo.TypeInformation; +import org.apache.flink.api.connector.sink2.Committer; +import org.apache.flink.api.connector.sink2.StatefulSink; +import org.apache.flink.configuration.Configuration; +import org.apache.flink.configuration.ReadableConfig; +import org.apache.flink.core.io.SimpleVersionedSerializer; +import org.apache.flink.streaming.api.connector.sink2.CommittableMessage; +import org.apache.flink.streaming.api.connector.sink2.CommittableWithLineage; +import org.apache.flink.streaming.api.connector.sink2.WithPostCommitTopology; +import org.apache.flink.streaming.api.connector.sink2.WithPreCommitTopology; +import org.apache.flink.streaming.api.connector.sink2.WithPreWriteTopology; +import org.apache.flink.streaming.api.datastream.DataStream; +import org.apache.flink.streaming.api.datastream.DataStreamSink; +import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator; +import org.apache.flink.streaming.api.operators.StreamingRuntimeContext; +import org.apache.flink.table.api.TableSchema; +import org.apache.flink.table.data.RowData; +import org.apache.flink.table.data.util.DataFormatConverters; +import org.apache.flink.table.types.DataType; +import org.apache.flink.table.types.logical.RowType; +import org.apache.flink.types.Row; +import org.apache.iceberg.DataFile; +import org.apache.iceberg.DistributionMode; +import org.apache.iceberg.FileFormat; +import org.apache.iceberg.PartitionField; +import org.apache.iceberg.PartitionSpec; +import org.apache.iceberg.Schema; +import org.apache.iceberg.SerializableTable; +import org.apache.iceberg.Table; +import org.apache.iceberg.common.DynFields; +import org.apache.iceberg.flink.FlinkConfigOptions; +import org.apache.iceberg.flink.FlinkSchemaUtil; +import org.apache.iceberg.flink.TableLoader; +import org.apache.iceberg.flink.sink.EqualityFieldKeySelector; +import org.apache.iceberg.flink.sink.PartitionKeySelector; +import org.apache.iceberg.flink.sink.RowDataTaskWriterFactory; +import org.apache.iceberg.flink.util.FlinkCompatibilityUtil; +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.Lists; +import org.apache.iceberg.relocated.com.google.common.collect.Maps; +import org.apache.iceberg.relocated.com.google.common.collect.Sets; +import org.apache.iceberg.types.TypeUtil; +import org.apache.iceberg.util.PropertyUtil; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import static org.apache.iceberg.TableProperties.DEFAULT_FILE_FORMAT; +import static org.apache.iceberg.TableProperties.DEFAULT_FILE_FORMAT_DEFAULT; +import static org.apache.iceberg.TableProperties.UPSERT_ENABLED; +import static org.apache.iceberg.TableProperties.UPSERT_ENABLED_DEFAULT; +import static org.apache.iceberg.TableProperties.WRITE_DISTRIBUTION_MODE; +import static org.apache.iceberg.TableProperties.WRITE_DISTRIBUTION_MODE_NONE; +import static org.apache.iceberg.TableProperties.WRITE_TARGET_FILE_SIZE_BYTES; +import static org.apache.iceberg.TableProperties.WRITE_TARGET_FILE_SIZE_BYTES_DEFAULT; + +public class FlinkSink implements StatefulSink<RowData, IcebergStreamWriterState>, + WithPreWriteTopology<RowData>, + WithPreCommitTopology<RowData, IcebergFlinkCommittable>, + WithPostCommitTopology<RowData, IcebergFlinkCommittable> { + private static final Logger LOG = LoggerFactory.getLogger(FlinkSink.class); + + private final TableLoader tableLoader; + private final Table table; + private final boolean overwrite; + private final boolean upsertMode; + private final DistributionMode distributionMode; + private final List<String> equalityFieldColumns; + private final List<Integer> equalityFieldIds; + private final int workerPoolSize; + private final String uidPrefix; + private final Map<String, String> snapshotProperties; + private final RowType flinkRowType; + + public FlinkSink(TableLoader tableLoader, + @Nullable Table newTable, + TableSchema tableSchema, + boolean overwrite, + DistributionMode distributionMode, + boolean upsert, + List<String> equalityFieldColumns, + @Nullable String uidPrefix, + ReadableConfig readableConfig, + Map<String, String> snapshotProperties) { + this.tableLoader = tableLoader; + this.overwrite = overwrite; + this.distributionMode = distributionMode; + this.equalityFieldColumns = equalityFieldColumns; + this.uidPrefix = uidPrefix == null ? "" : uidPrefix; + this.snapshotProperties = snapshotProperties; + + Preconditions.checkNotNull(tableLoader, "Table loader shouldn't be null"); + + if (newTable == null) { + tableLoader.open(); + try (TableLoader loader = tableLoader) { + this.table = loader.loadTable(); + } catch (IOException e) { + throw new UncheckedIOException("Failed to load iceberg table from table loader: " + tableLoader, e); + } + } else { + this.table = newTable; + } + + this.workerPoolSize = readableConfig.get(FlinkConfigOptions.TABLE_EXEC_ICEBERG_WORKER_POOL_SIZE); + this.equalityFieldIds = checkAndGetEqualityFieldIds(table, equalityFieldColumns); + + this.flinkRowType = toFlinkRowType(table.schema(), tableSchema); + + // Fallback to use upsert mode parsed from table properties if don't specify in job level. + this.upsertMode = upsert || PropertyUtil.propertyAsBoolean(table.properties(), + UPSERT_ENABLED, UPSERT_ENABLED_DEFAULT); + + // Validate the equality fields and partition fields if we enable the upsert mode. + if (upsertMode) { + Preconditions.checkState( + !overwrite, + "OVERWRITE mode shouldn't be enable when configuring to use UPSERT data stream."); + Preconditions.checkState( + !equalityFieldIds.isEmpty(), + "Equality field columns shouldn't be empty when configuring to use UPSERT data stream."); + if (!table.spec().isUnpartitioned()) { + for (PartitionField partitionField : table.spec().fields()) { + Preconditions.checkState(equalityFieldIds.contains(partitionField.sourceId()), + "In UPSERT mode, partition field '%s' should be included in equality fields: '%s'", + partitionField, equalityFieldColumns); + } + } + } + } + + @Override + public DataStream<RowData> addPreWriteTopology(DataStream<RowData> inputDataStream) { + return distributeDataStream(inputDataStream, table.properties(), equalityFieldIds, table.spec(), + table.schema(), flinkRowType, distributionMode, equalityFieldColumns); + } + + @Override + public IcebergStreamWriter createWriter(InitContext context) { + return restoreWriter(context, null); + } + + @Override + public IcebergStreamWriter restoreWriter(InitContext context, + Collection<IcebergStreamWriterState> recoveredState) { + StreamingRuntimeContext runtimeContext = runtimeContextHidden(context); + int attemptNumber = runtimeContext.getAttemptNumber(); + String jobId = runtimeContext.getJobId().toString(); + IcebergStreamWriter streamWriter = createStreamWriter(table, flinkRowType, equalityFieldIds, + upsertMode, jobId, context.getSubtaskId(), attemptNumber); + if (recoveredState == null) { + return streamWriter; + } + return streamWriter.restoreWriter(recoveredState); + } + + @Override + public SimpleVersionedSerializer<IcebergStreamWriterState> getWriterStateSerializer() { + return new IcebergStreamWriterStateSerializer<>(); + } + + static IcebergStreamWriter createStreamWriter(Table table, + RowType flinkRowType, + List<Integer> equalityFieldIds, + boolean upsert, + String jobId, + int subTaskId, + long attemptId) { + Map<String, String> props = table.properties(); + long targetFileSize = PropertyUtil.propertyAsLong(props, WRITE_TARGET_FILE_SIZE_BYTES, + WRITE_TARGET_FILE_SIZE_BYTES_DEFAULT); + + RowDataTaskWriterFactory taskWriterFactory = new RowDataTaskWriterFactory(SerializableTable.copyOf(table), + flinkRowType, targetFileSize, getFileFormat(props), equalityFieldIds, upsert); + + return new IcebergStreamWriter(table.name(), taskWriterFactory, jobId, subTaskId, attemptId); + } + + @Override + public DataStream<CommittableMessage<IcebergFlinkCommittable>> addPreCommitTopology( + DataStream<CommittableMessage<IcebergFlinkCommittable>> writeResults) { + return writeResults.map(new RichMapFunction<CommittableMessage<IcebergFlinkCommittable>, + CommittableMessage<IcebergFlinkCommittable>>() { + @Override + public CommittableMessage<IcebergFlinkCommittable> map(CommittableMessage<IcebergFlinkCommittable> message) { + if (message instanceof CommittableWithLineage) { + CommittableWithLineage<IcebergFlinkCommittable> committableWithLineage = + (CommittableWithLineage<IcebergFlinkCommittable>) message; + IcebergFlinkCommittable committable = committableWithLineage.getCommittable(); + committable.checkpointId(committableWithLineage.getCheckpointId().orElse(0)); + committable.subtaskId(committableWithLineage.getSubtaskId()); + committable.jobID(getRuntimeContext().getJobId().toString()); + } + return message; + } + }).uid(uidPrefix + "pre-commit-topology").global(); + } + + @Override + public Committer<IcebergFlinkCommittable> createCommitter() { + return new IcebergFilesCommitter(tableLoader, overwrite, snapshotProperties, workerPoolSize); + } + + @Override + public SimpleVersionedSerializer<IcebergFlinkCommittable> getCommittableSerializer() { + return new IcebergFlinkCommittableSerializer(); + } + + @Override + public void addPostCommitTopology(DataStream<CommittableMessage<IcebergFlinkCommittable>> committables) { + // TODO Support small file compaction + } + + private StreamingRuntimeContext runtimeContextHidden(InitContext context) { + DynFields.BoundField<StreamingRuntimeContext> runtimeContextBoundField = + DynFields.builder().hiddenImpl(context.getClass(), "runtimeContext").build(context); + return runtimeContextBoundField.get(); + } + + private static FileFormat getFileFormat(Map<String, String> properties) { + String formatString = properties.getOrDefault(DEFAULT_FILE_FORMAT, DEFAULT_FILE_FORMAT_DEFAULT); + return FileFormat.valueOf(formatString.toUpperCase(Locale.ENGLISH)); + } + + /** + * Initialize a {@link Builder} to export the data from generic input data stream into iceberg table. We use + * {@link RowData} inside the sink connector, so users need to provide a mapper function and a + * {@link TypeInformation} to convert those generic records to a RowData DataStream. + * + * @param input the generic source input data stream. + * @param mapper function to convert the generic data to {@link RowData} + * @param outputType to define the {@link TypeInformation} for the input data. + * @param <T> the data type of records. + * @return {@link Builder} to connect the iceberg table. + */ + public static <T> Builder builderFor(DataStream<T> input, + MapFunction<T, RowData> mapper, + TypeInformation<RowData> outputType) { + return new Builder().forMapperOutputType(input, mapper, outputType); + } + + /** + * Initialize a {@link Builder} to export the data from input data stream with {@link Row}s into iceberg table. We use + * {@link RowData} inside the sink connector, so users need to provide a {@link TableSchema} for builder to convert + * those {@link Row}s to a {@link RowData} DataStream. + * + * @param input the source input data stream with {@link Row}s. + * @param tableSchema defines the {@link TypeInformation} for input data. + * @return {@link Builder} to connect the iceberg table. + */ + public static Builder forRow(DataStream<Row> input, TableSchema tableSchema) { + RowType rowType = (RowType) tableSchema.toRowDataType().getLogicalType(); + DataType[] fieldDataTypes = tableSchema.getFieldDataTypes(); + + DataFormatConverters.RowConverter rowConverter = new DataFormatConverters.RowConverter(fieldDataTypes); + return builderFor(input, rowConverter::toInternal, FlinkCompatibilityUtil.toTypeInfo(rowType)) + .tableSchema(tableSchema); + } + + /** + * Initialize a {@link Builder} to export the data from input data stream with {@link RowData}s into iceberg table. + * + * @param input the source input data stream with {@link RowData}s. + * @return {@link Builder} to connect the iceberg table. + */ + public static Builder forRowData(DataStream<RowData> input) { + return new Builder().forRowData(input); + } + + /** + * Initialize a {@link Builder} to export the data from input data stream with {@link RowData}s into iceberg table. + * + * @return {@link Builder} to connect the iceberg table. + */ + public static Builder builder() { + return new Builder(); + } + + public static class Builder { + private Function<String, DataStream<RowData>> inputCreator = null; + private TableLoader tableLoader; + private Table table; + private TableSchema tableSchema; + private boolean overwrite = false; + private DistributionMode distributionMode = null; + private Integer writeParallelism = null; + private boolean upsert = false; + private List<String> equalityFieldColumns = null; + private String uidPrefix = "iceberg-flink-job"; + private final Map<String, String> snapshotProperties = Maps.newHashMap(); + private ReadableConfig readableConfig = new Configuration(); + + private Builder() { + } + + private Builder forRowData(DataStream<RowData> newRowDataInput) { + this.inputCreator = ignored -> newRowDataInput; + return this; + } + + private <T> Builder forMapperOutputType(DataStream<T> input, + MapFunction<T, RowData> mapper, + TypeInformation<RowData> outputType) { + this.inputCreator = newUidPrefix -> { + // Input stream order is crucial for some situation(e.g. in cdc case). + // Therefore, we need to set the parallelismof map operator same as its input to keep map operator + // chaining its input, and avoid rebalanced by default. + SingleOutputStreamOperator<RowData> inputStream = input.map(mapper, outputType) + .setParallelism(input.getParallelism()); + if (newUidPrefix != null) { + inputStream.name(Builder.this.operatorName(newUidPrefix)).uid(newUidPrefix + "-mapper"); + } + return inputStream; + }; + return this; + } + + /** + * This iceberg {@link Table} instance is used for initializing {@link IcebergStreamWriter} which will write all + * the records into {@link DataFile}s and emit them to downstream operator. Providing a table would avoid so many + * table loading from each separate task. + * + * @param newTable the loaded iceberg table instance. + * @return {@link Builder} to connect the iceberg table. + */ + public Builder table(Table newTable) { + this.table = newTable; + return this; + } + + /** + * The table loader is used for loading tables in {@link IcebergFilesCommitter} lazily, we need this loader because + * {@link Table} is not serializable and could not just use the loaded table from Builder#table in the remote task + * manager. + * + * @param newTableLoader to load iceberg table inside tasks. + * @return {@link Builder} to connect the iceberg table. + */ + public Builder tableLoader(TableLoader newTableLoader) { + this.tableLoader = newTableLoader; + return this; + } + + public Builder tableSchema(TableSchema newTableSchema) { + this.tableSchema = newTableSchema; + return this; + } + + public Builder overwrite(boolean newOverwrite) { + this.overwrite = newOverwrite; + return this; + } + + public Builder flinkConf(ReadableConfig config) { + this.readableConfig = config; + return this; + } + + /** + * Configure the write {@link DistributionMode} that the flink sink will use. Currently, flink support + * {@link DistributionMode#NONE} and {@link DistributionMode#HASH}. + * + * @param mode to specify the write distribution mode. + * @return {@link Builder} to connect the iceberg table. + */ + public Builder distributionMode(DistributionMode mode) { + Preconditions.checkArgument( + !DistributionMode.RANGE.equals(mode), + "Flink does not support 'range' write distribution mode now."); + this.distributionMode = mode; + return this; + } + + /** + * Configuring the write parallel number for iceberg stream writer. + * + * @param newWriteParallelism the number of parallel iceberg stream writer. + * @return {@link Builder} to connect the iceberg table. + */ + public Builder writeParallelism(int newWriteParallelism) { + this.writeParallelism = newWriteParallelism; + return this; + } + + /** + * All INSERT/UPDATE_AFTER events from input stream will be transformed to UPSERT events, which means it will + * DELETE the old records and then INSERT the new records. In partitioned table, the partition fields should be + * a subset of equality fields, otherwise the old row that located in partition-A could not be deleted by the + * new row that located in partition-B. + * + * @param enabled indicate whether it should transform all INSERT/UPDATE_AFTER events to UPSERT. + * @return {@link Builder} to connect the iceberg table. + */ + public Builder upsert(boolean enabled) { + this.upsert = enabled; + return this; + } + + /** + * Configuring the equality field columns for iceberg table that accept CDC or UPSERT events. + * + * @param columns defines the iceberg table's key. + * @return {@link Builder} to connect the iceberg table. + */ + public Builder equalityFieldColumns(List<String> columns) { + this.equalityFieldColumns = columns; + return this; + } + + /** + * Set the uid prefix for FlinkSink operators. Note that FlinkSink internally consists of multiple operators (like + * writer, committer, dummy sink etc.) Actually operator uid will be appended with a suffix like "uidPrefix-writer". + * <br><br> + * If provided, this prefix is also applied to operator names. + * <br><br> + * Flink auto generates operator uid if not set explicitly. It is a recommended + * <a href="https://ci.apache.org/projects/flink/flink-docs-master/docs/ops/production_ready/";> + * best-practice to set uid for all operators</a> before deploying to production. Flink has an option to {@code + * pipeline.auto-generate-uid=false} to disable auto-generation and force explicit setting of all operator uid. + * <br><br> + * Be careful with setting this for an existing job, because now we are changing the operator uid from an + * auto-generated one to this new value. When deploying the change with a checkpoint, Flink won't be able to restore + * the previous Flink sink operator state (more specifically the committer operator state). You need to use {@code + * --allowNonRestoredState} to ignore the previous sink state. During restore Flink sink state is used to check if + * last commit was actually successful or not. {@code --allowNonRestoredState} can lead to data loss if the + * Iceberg commit failed in the last completed checkpoint. + * + * @param newPrefix prefix for Flink sink operator uid and name + * @return {@link Builder} to connect the iceberg table. + */ + public Builder uidPrefix(String newPrefix) { + this.uidPrefix = newPrefix; + return this; + } + + public Builder setSnapshotProperties(Map<String, String> properties) { + snapshotProperties.putAll(properties); + return this; + } + + public Builder setSnapshotProperty(String property, String value) { + snapshotProperties.put(property, value); + return this; + } + + /** + * Append the iceberg sink operators to write records to iceberg table. + */ + @SuppressWarnings("unchecked") + public DataStreamSink<Void> append() { + Preconditions.checkArgument( + inputCreator != null, + "Please use forRowData() or forMapperOutputType() to initialize the input DataStream."); + Preconditions.checkNotNull(tableLoader, "Table loader shouldn't be null"); + + DataStream<RowData> rowDataInput = inputCreator.apply(uidPrefix); + DataStreamSink rowDataDataStreamSink = rowDataInput.sinkTo(build()).uid(uidPrefix + "-sink"); + if (writeParallelism != null) { + rowDataDataStreamSink.setParallelism(writeParallelism); + } + return rowDataDataStreamSink; + } + + public FlinkSink build() { + return new FlinkSink(tableLoader, table, tableSchema, overwrite, distributionMode, upsert, equalityFieldColumns, + uidPrefix, readableConfig, snapshotProperties); + } + + private String operatorName(String suffix) { + return uidPrefix != null ? uidPrefix + "-" + suffix : suffix; + } + + @VisibleForTesting + List<Integer> checkAndGetEqualityFieldIds() { + List<Integer> equalityFieldIds = Lists.newArrayList(table.schema().identifierFieldIds()); + if (equalityFieldColumns != null && equalityFieldColumns.size() > 0) { + Set<Integer> equalityFieldSet = Sets.newHashSetWithExpectedSize(equalityFieldColumns.size()); + for (String column : equalityFieldColumns) { + org.apache.iceberg.types.Types.NestedField field = table.schema().findField(column); + Preconditions.checkNotNull(field, "Missing required equality field column '%s' in table schema %s", + column, table.schema()); + equalityFieldSet.add(field.fieldId()); + } + + if (!equalityFieldSet.equals(table.schema().identifierFieldIds())) { + LOG.warn("The configured equality field column IDs {} are not matched with the schema identifier field IDs" + + " {}, use job specified equality field columns as the equality fields by default.", + equalityFieldSet, table.schema().identifierFieldIds()); + } + equalityFieldIds = Lists.newArrayList(equalityFieldSet); + } + return equalityFieldIds; + } + } + + static RowType toFlinkRowType(Schema schema, TableSchema requestedSchema) { + if (requestedSchema != null) { + // Convert the flink schema to iceberg schema firstly, then reassign ids to match the existing iceberg schema. + Schema writeSchema = TypeUtil.reassignIds(FlinkSchemaUtil.convert(requestedSchema), schema); + TypeUtil.validateWriteSchema(schema, writeSchema, true, true); + + // We use this flink schema to read values from RowData. The flink's TINYINT and SMALLINT will be promoted to + // iceberg INTEGER, that means if we use iceberg's table schema to read TINYINT (backend by 1 'byte'), we will + // read 4 bytes rather than 1 byte, it will mess up the byte array in BinaryRowData. So here we must use flink + // schema. + return (RowType) requestedSchema.toRowDataType().getLogicalType(); + } else { + return FlinkSchemaUtil.convert(schema); + } + } + + static DataStream<RowData> distributeDataStream(DataStream<RowData> input, + Map<String, String> properties, + List<Integer> equalityFieldIds, + PartitionSpec partitionSpec, + Schema iSchema, + RowType flinkRowType, + DistributionMode distributionMode, + List<String> equalityFieldColumns) { + DistributionMode writeMode; + if (distributionMode == null) { + // Fallback to use distribution mode parsed from table properties if don't specify in job level. + String modeName = PropertyUtil.propertyAsString( + properties, + WRITE_DISTRIBUTION_MODE, + WRITE_DISTRIBUTION_MODE_NONE); + + writeMode = DistributionMode.fromName(modeName); + } else { + writeMode = distributionMode; + } + + LOG.info("Write distribution mode is '{}'", writeMode.modeName()); + switch (writeMode) { + case NONE: + if (equalityFieldIds.isEmpty()) { + return input; + } else { + LOG.info("Distribute rows by equality fields, because there are equality fields set"); + return input.keyBy(new EqualityFieldKeySelector(iSchema, flinkRowType, equalityFieldIds)); + } + + case HASH: + if (equalityFieldIds.isEmpty()) { + if (partitionSpec.isUnpartitioned()) { + LOG.warn("Fallback to use 'none' distribution mode, because there are no equality fields set " + + "and table is unpartitioned"); + return input; + } else { + return input.keyBy(new PartitionKeySelector(partitionSpec, iSchema, flinkRowType)); + } + } else { + if (partitionSpec.isUnpartitioned()) { + LOG.info("Distribute rows by equality fields, because there are equality fields set " + + "and table is unpartitioned"); + return input.keyBy(new EqualityFieldKeySelector(iSchema, flinkRowType, equalityFieldIds)); + } else { + for (PartitionField partitionField : partitionSpec.fields()) { + Preconditions.checkState(equalityFieldIds.contains(partitionField.sourceId()), + "In 'hash' distribution mode with equality fields set, partition field '%s' " + + "should be included in equality fields: '%s'", partitionField, equalityFieldColumns); + } + return input.keyBy(new PartitionKeySelector(partitionSpec, iSchema, flinkRowType)); Review Comment: Good question. When we have more equality fields than the partition fields, will it cause data distribution errors if we use EqualityFieldKeySelector? -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: issues-unsubscr...@iceberg.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@iceberg.apache.org For additional commands, e-mail: issues-h...@iceberg.apache.org
