garyli1019 commented on a change in pull request #2430:
URL: https://github.com/apache/hudi/pull/2430#discussion_r560683106
##########
File path:
hudi-common/src/main/java/org/apache/hudi/common/model/OverwriteWithLatestAvroPayload.java
##########
@@ -79,7 +79,12 @@ public OverwriteWithLatestAvroPayload
preCombine(OverwriteWithLatestAvroPayload
* @returns {@code true} if record represents a delete record. {@code false}
otherwise.
*/
protected boolean isDeleteRecord(GenericRecord genericRecord) {
- Object deleteMarker = genericRecord.get("_hoodie_is_deleted");
+ final String isDeleteKey = "_hoodie_is_deleted";
+ // Modify to be compatible with old version Avro.
+ if (genericRecord.getSchema().getField(isDeleteKey) == null) {
Review comment:
What does the old version Avro mean here? This seems like being handled
by the check on return
##########
File path: hudi-flink/src/main/java/org/apache/hudi/operator/FlinkOptions.java
##########
@@ -0,0 +1,249 @@
+/*
+ * 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.hudi.operator;
+
+import org.apache.hudi.config.HoodieWriteConfig;
+import org.apache.hudi.streamer.FlinkStreamerConfig;
+import org.apache.hudi.common.model.OverwriteWithLatestAvroPayload;
+import org.apache.hudi.keygen.SimpleAvroKeyGenerator;
+import org.apache.hudi.keygen.constant.KeyGeneratorOptions;
+import org.apache.hudi.util.StreamerUtil;
+
+import org.apache.flink.configuration.ConfigOption;
+import org.apache.flink.configuration.ConfigOptions;
+import org.apache.flink.configuration.Configuration;
+
+import java.util.Arrays;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+
+/**
+ * Hoodie Flink config options.
+ *
+ * <p>It has the options for Hoodie table read and write. It also defines some
utilities.
+ */
+public class FlinkOptions {
+ private FlinkOptions() {
+ }
+
+ // ------------------------------------------------------------------------
+ // Base Options
+ // ------------------------------------------------------------------------
+ public static final ConfigOption<String> PATH = ConfigOptions
+ .key("path")
+ .stringType()
+ .noDefaultValue()
+ .withDescription("Base path for the target hoodie table."
+ + "\nThe path would be created if it does not exist,\n"
+ + "otherwise a Hoodie table expects to be initialized successfully");
+
+ public static final ConfigOption<String> PROPS_FILE_PATH = ConfigOptions
+ .key("properties-file.path")
+ .stringType()
+ .noDefaultValue()
+ .withDescription("Path to properties file on local-fs or dfs, with
configurations for \n"
+ + "hoodie client, schema provider, key generator and data source.
For hoodie client props, sane defaults are\n"
+ + "used, but recommend use to provide basic things like metrics
endpoints, hive configs etc. For sources, refer\n"
+ + "to individual classes, for supported properties");
+
+ // ------------------------------------------------------------------------
+ // Read Options
+ // ------------------------------------------------------------------------
+ public static final ConfigOption<String> READ_SCHEMA_FILE_PATH =
ConfigOptions
+ .key("read.schema.file.path")
+ .stringType()
+ .noDefaultValue()
+ .withDescription("Avro schema file path, the parsed schema is used for
deserializing");
+
+ // ------------------------------------------------------------------------
+ // Write Options
+ // ------------------------------------------------------------------------
+ public static final ConfigOption<String> TABLE_NAME = ConfigOptions
+ .key(HoodieWriteConfig.TABLE_NAME)
+ .stringType()
+ .noDefaultValue()
+ .withDescription("Table name to register to Hive metastore");
+
+ public static final ConfigOption<String> TABLE_TYPE = ConfigOptions
+ .key("write.table.type")
+ .stringType()
+ .defaultValue("COPY_ON_WRITE")
+ .withDescription("Type of table to write. COPY_ON_WRITE (or)
MERGE_ON_READ");
+
+ public static final ConfigOption<String> OPERATION = ConfigOptions
+ .key("write.operation")
+ .stringType()
+ .defaultValue("upsert")
+ .withDescription("The write operation, that this write should do");
+
+ public static final ConfigOption<String> PRECOMBINE_FIELD = ConfigOptions
+ .key("write.precombine.field")
Review comment:
this is also available in `HoodieWriteConfig`, payload, kengen as well.
If the config is commonly used by both engines, I think we could add new items
to `HoodieWriteConfig` as well.
##########
File path: hudi-flink/src/main/java/org/apache/hudi/operator/FlinkOptions.java
##########
@@ -0,0 +1,249 @@
+/*
+ * 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.hudi.operator;
+
+import org.apache.hudi.config.HoodieWriteConfig;
+import org.apache.hudi.streamer.FlinkStreamerConfig;
+import org.apache.hudi.common.model.OverwriteWithLatestAvroPayload;
+import org.apache.hudi.keygen.SimpleAvroKeyGenerator;
+import org.apache.hudi.keygen.constant.KeyGeneratorOptions;
+import org.apache.hudi.util.StreamerUtil;
+
+import org.apache.flink.configuration.ConfigOption;
+import org.apache.flink.configuration.ConfigOptions;
+import org.apache.flink.configuration.Configuration;
+
+import java.util.Arrays;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+
+/**
+ * Hoodie Flink config options.
+ *
+ * <p>It has the options for Hoodie table read and write. It also defines some
utilities.
+ */
+public class FlinkOptions {
+ private FlinkOptions() {
+ }
+
+ // ------------------------------------------------------------------------
+ // Base Options
+ // ------------------------------------------------------------------------
+ public static final ConfigOption<String> PATH = ConfigOptions
+ .key("path")
+ .stringType()
+ .noDefaultValue()
+ .withDescription("Base path for the target hoodie table."
+ + "\nThe path would be created if it does not exist,\n"
+ + "otherwise a Hoodie table expects to be initialized successfully");
+
+ public static final ConfigOption<String> PROPS_FILE_PATH = ConfigOptions
+ .key("properties-file.path")
+ .stringType()
+ .noDefaultValue()
+ .withDescription("Path to properties file on local-fs or dfs, with
configurations for \n"
+ + "hoodie client, schema provider, key generator and data source.
For hoodie client props, sane defaults are\n"
+ + "used, but recommend use to provide basic things like metrics
endpoints, hive configs etc. For sources, refer\n"
+ + "to individual classes, for supported properties");
+
+ // ------------------------------------------------------------------------
+ // Read Options
+ // ------------------------------------------------------------------------
+ public static final ConfigOption<String> READ_SCHEMA_FILE_PATH =
ConfigOptions
+ .key("read.schema.file.path")
+ .stringType()
+ .noDefaultValue()
+ .withDescription("Avro schema file path, the parsed schema is used for
deserializing");
+
+ // ------------------------------------------------------------------------
+ // Write Options
+ // ------------------------------------------------------------------------
+ public static final ConfigOption<String> TABLE_NAME = ConfigOptions
+ .key(HoodieWriteConfig.TABLE_NAME)
+ .stringType()
+ .noDefaultValue()
+ .withDescription("Table name to register to Hive metastore");
+
+ public static final ConfigOption<String> TABLE_TYPE = ConfigOptions
+ .key("write.table.type")
+ .stringType()
+ .defaultValue("COPY_ON_WRITE")
+ .withDescription("Type of table to write. COPY_ON_WRITE (or)
MERGE_ON_READ");
+
+ public static final ConfigOption<String> OPERATION = ConfigOptions
+ .key("write.operation")
+ .stringType()
+ .defaultValue("upsert")
+ .withDescription("The write operation, that this write should do");
+
+ public static final ConfigOption<String> PRECOMBINE_FIELD = ConfigOptions
+ .key("write.precombine.field")
+ .stringType()
+ .defaultValue("ts")
+ .withDescription("Field used in preCombining before actual write. When
two records have the same\n"
+ + "key value, we will pick the one with the largest value for the
precombine field,\n"
+ + "determined by Object.compareTo(..)");
+
+ public static final ConfigOption<String> PAYLOAD_CLASS = ConfigOptions
+ .key("write.payload.class")
+ .stringType()
+ .defaultValue(OverwriteWithLatestAvroPayload.class.getName())
+ .withDescription("Payload class used. Override this, if you like to roll
your own merge logic, when upserting/inserting.\n"
+ + "This will render any value set for the option in-effective");
+
+ /**
+ * Flag to indicate whether to drop duplicates upon insert.
+ * By default insert will accept duplicates, to gain extra performance.
+ */
+ public static final ConfigOption<Boolean> INSERT_DROP_DUPS = ConfigOptions
+ .key("write.insert.drop.duplicates")
+ .booleanType()
+ .defaultValue(false)
+ .withDescription("Flag to indicate whether to drop duplicates upon
insert.\n"
+ + "By default insert will accept duplicates, to gain extra
performance");
+
+ public static final ConfigOption<Integer> RETRY_TIMES = ConfigOptions
+ .key("write.retry.times")
+ .intType()
+ .defaultValue(3)
+ .withDescription("Flag to indicate how many times streaming job should
retry for a failed checkpoint batch.\n"
+ + "By default 3");
+
+ public static final ConfigOption<Long> RETRY_INTERVAL_MS = ConfigOptions
+ .key("write.retry.interval.ms")
+ .longType()
+ .defaultValue(2000L)
+ .withDescription("Flag to indicate how long (by millisecond) before a
retry should issued for failed checkpoint batch.\n"
+ + "By default 2000 and it will be doubled by every retry");
+
+ public static final ConfigOption<Boolean> IGNORE_FAILED_BATCH = ConfigOptions
+ .key("write.ignore.failed.batch")
+ .booleanType()
+ .defaultValue(true)
+ .withDescription("Flag to indicate whether to ignore any non exception
error (e.g. writestatus error). within a checkpoint batch.\n"
+ + "By default true (in favor of streaming progressing over data
integrity)");
+
+ public static final ConfigOption<String> RECORD_KEY_FIELD = ConfigOptions
+ .key(KeyGeneratorOptions.RECORDKEY_FIELD_OPT_KEY)
+ .stringType()
+ .defaultValue("uuid")
+ .withDescription("Record key field. Value to be used as the `recordKey`
component of `HoodieKey`.\n"
+ + "Actual value will be obtained by invoking .toString() on the
field value. Nested fields can be specified using "
+ + "the dot notation eg: `a.b.c`");
+
+ public static final ConfigOption<String> PARTITION_PATH_FIELD = ConfigOptions
+ .key(KeyGeneratorOptions.PARTITIONPATH_FIELD_OPT_KEY)
+ .stringType()
+ .defaultValue("partition-path")
+ .withDescription("Partition path field. Value to be used at the
`partitionPath` component of `HoodieKey`.\n"
+ + "Actual value obtained by invoking .toString()");
+
+ public static final ConfigOption<String> KEYGEN_CLASS = ConfigOptions
+ .key("hoodie.datasource.write.keygenerator.class")
+ .stringType()
+ .defaultValue(SimpleAvroKeyGenerator.class.getName())
+ .withDescription("Key generator class, that implements will extract the
key out of incoming record");
+
+ public static final ConfigOption<Integer> WRITE_TASK_PARALLELISM =
ConfigOptions
+ .key("write.task.parallelism")
+ .intType()
+ .defaultValue(4)
+ .withDescription("Parallelism of tasks that do actual write, default is
4");
+
Review comment:
maybe add another config to specify index type?
##########
File path:
hudi-flink/src/main/java/org/apache/hudi/operator/StreamWriteOperatorCoordinator.java
##########
@@ -0,0 +1,419 @@
+/*
+ * 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.hudi.operator;
+
+import org.apache.hudi.client.FlinkTaskContextSupplier;
+import org.apache.hudi.client.HoodieFlinkWriteClient;
+import org.apache.hudi.client.WriteStatus;
+import org.apache.hudi.client.common.HoodieFlinkEngineContext;
+import org.apache.hudi.common.fs.FSUtils;
+import org.apache.hudi.common.model.HoodieTableType;
+import org.apache.hudi.common.table.HoodieTableMetaClient;
+import org.apache.hudi.common.util.Option;
+import org.apache.hudi.exception.HoodieException;
+import org.apache.hudi.operator.event.BatchWriteSuccessEvent;
+import org.apache.hudi.util.StreamerUtil;
+
+import org.apache.flink.annotation.VisibleForTesting;
+import org.apache.flink.configuration.Configuration;
+import org.apache.flink.core.memory.DataInputViewStreamWrapper;
+import org.apache.flink.core.memory.DataOutputViewStreamWrapper;
+import org.apache.flink.runtime.jobgraph.OperatorID;
+import org.apache.flink.runtime.operators.coordination.OperatorCoordinator;
+import org.apache.flink.runtime.operators.coordination.OperatorEvent;
+import org.apache.flink.util.Preconditions;
+import org.apache.hadoop.fs.FileSystem;
+import org.apache.hadoop.fs.Path;
+import org.jetbrains.annotations.Nullable;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import java.io.ByteArrayInputStream;
+import java.io.ByteArrayOutputStream;
+import java.io.DataInputStream;
+import java.io.DataOutputStream;
+import java.io.IOException;
+import java.util.Arrays;
+import java.util.Collection;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Objects;
+import java.util.concurrent.CompletableFuture;
+import java.util.concurrent.CompletionException;
+import java.util.concurrent.TimeUnit;
+import java.util.stream.Collectors;
+
+/**
+ * {@link OperatorCoordinator} for {@link StreamWriteFunction}.
+ *
+ * <p>This coordinator starts a new instant when a new checkpoint starts. It
commits the instant when all the
+ * operator tasks write the buffer successfully for a round of checkpoint.
+ *
+ * <p>If there is no data for a round of checkpointing, it rolls back the
metadata.
+ *
+ * @see StreamWriteFunction for the work flow and semantics
+ */
+public class StreamWriteOperatorCoordinator
+ implements OperatorCoordinator {
+ private static final Logger LOG =
LoggerFactory.getLogger(StreamWriteOperatorCoordinator.class);
+
+ /**
+ * Config options.
+ */
+ private final Configuration conf;
+
+ /**
+ * Write client.
+ */
+ private transient HoodieFlinkWriteClient writeClient;
+
+ private long inFlightCheckpoint = -1;
+
+ /**
+ * Current REQUESTED instant, for validation.
+ */
+ private String inFlightInstant = "";
+
+ /**
+ * Event buffer for one round of checkpointing. When all the elements are
non-null and have the same
+ * write instant, then the instant succeed and we can commit it.
+ */
+ private transient BatchWriteSuccessEvent[] eventBuffer;
+
+ /**
+ * Task number of the operator.
+ */
+ private final int parallelism;
+
+ /**
+ * Constructs a StreamingSinkOperatorCoordinator.
+ *
+ * @param conf The config options
+ * @param parallelism The operator task number
+ */
+ public StreamWriteOperatorCoordinator(
+ Configuration conf,
+ int parallelism) {
+ this.conf = conf;
+ this.parallelism = parallelism;
+ }
+
+ @Override
+ public void start() throws Exception {
+ // initialize event buffer
+ reset();
+ // writeClient
+ initWriteClient();
+ // init table, create it if not exists.
+ initTable();
+ }
+
+ @Override
+ public void close() {
+ if (writeClient != null) {
+ writeClient.close();
+ }
+ this.eventBuffer = null;
+ }
+
+ @Override
+ public void checkpointCoordinator(long checkpointId,
CompletableFuture<byte[]> result) {
+ try {
+ final String errMsg = "A new checkpoint starts while the last checkpoint
buffer"
+ + " data has not finish writing, roll back the last write and throw";
+ checkAndForceCommit(errMsg);
+ this.inFlightInstant = this.writeClient.startCommit();
+ this.inFlightCheckpoint = checkpointId;
+ LOG.info("Create instant [{}], at checkpoint [{}]",
this.inFlightInstant, checkpointId);
+ result.complete(writeCheckpointBytes());
+ } catch (Throwable throwable) {
+ // when a checkpoint fails, throws directly.
+ result.completeExceptionally(
+ new CompletionException(
+ String.format("Failed to checkpoint Instant %s for source %s",
+ this.inFlightInstant, this.getClass().getSimpleName()),
throwable));
+ }
+ }
+
+ @Override
+ public void notifyCheckpointComplete(long checkpointId) {
+ // start to commit the instant.
+ checkAndCommitWithRetry();
+ }
+
+ @Override
+ public void notifyCheckpointAborted(long checkpointId) {
+ Preconditions.checkState(inFlightCheckpoint == checkpointId,
+ "The aborted checkpoint should always be the last checkpoint");
+ checkAndForceCommit("The last checkpoint was aborted, roll back the last
write and throw");
+ }
+
+ @Override
+ public void resetToCheckpoint(long l, @Nullable byte[] checkpointData)
throws Exception {
+ if (checkpointData != null) {
+ // restore when any checkpoint completed
+ deserializeCheckpointAndRestore(checkpointData);
+ }
+ }
+
+ @Override
+ public void handleEventFromOperator(int i, OperatorEvent operatorEvent) {
+ // no event to handle
+ Preconditions.checkState(operatorEvent instanceof BatchWriteSuccessEvent,
+ "The coordinator can only handle BatchWriteSuccessEvent");
+ BatchWriteSuccessEvent event = (BatchWriteSuccessEvent) operatorEvent;
+
Preconditions.checkState(event.getInstantTime().equals(this.inFlightInstant),
+ String.format("Receive an unexpected event for instant %s from task
%d",
+ event.getInstantTime(), event.getTaskID()));
+ this.eventBuffer[event.getTaskID()] = event;
+ }
+
+ @Override
+ public void subtaskFailed(int i, @Nullable Throwable throwable) {
+ // no operation
+ }
+
+ @Override
+ public void subtaskReset(int i, long l) {
+ // no operation
+ }
+
+ // -------------------------------------------------------------------------
+ // Utilities
+ // -------------------------------------------------------------------------
+
+ @SuppressWarnings("rawtypes")
+ private void initWriteClient() {
+ writeClient = new HoodieFlinkWriteClient(
+ new HoodieFlinkEngineContext(new FlinkTaskContextSupplier(null)),
+ StreamerUtil.getHoodieClientConfig(this.conf),
+ true);
+ }
+
+ private void initTable() throws IOException {
+ final String basePath = this.conf.getString(FlinkOptions.PATH);
+ final org.apache.hadoop.conf.Configuration hadoopConf =
StreamerUtil.getHadoopConf();
+ // Hadoop FileSystem
+ try (FileSystem fs = FSUtils.getFs(basePath, hadoopConf)) {
+ if (!fs.exists(new Path(basePath,
HoodieTableMetaClient.METAFOLDER_NAME))) {
+ HoodieTableMetaClient.initTableType(
+ hadoopConf,
+ basePath,
+
HoodieTableType.valueOf(this.conf.getString(FlinkOptions.TABLE_TYPE)),
+ this.conf.getString(FlinkOptions.TABLE_NAME),
+ "archived",
+ this.conf.getString(FlinkOptions.PAYLOAD_CLASS),
+ 1);
+ LOG.info("Table initialized");
+ } else {
+ LOG.info("Table [{}/{}] already exists, no need to initialize the
table",
+ basePath, this.conf.getString(FlinkOptions.TABLE_NAME));
+ }
+ }
+ }
+
+ static byte[] readBytes(DataInputStream in, int size) throws IOException {
+ byte[] bytes = new byte[size];
+ in.readFully(bytes);
+ return bytes;
+ }
+
+ /**
+ * Serialize the coordinator state. The current implementation may not be
super efficient,
+ * but it should not matter that much because most of the state should be
rather small.
+ * Large states themselves may already be a problem regardless of how the
serialization
+ * is implemented.
+ *
+ * @return A byte array containing the serialized state of the source
coordinator.
+ * @throws IOException When something goes wrong in serialization.
+ */
+ private byte[] writeCheckpointBytes() throws IOException {
+ try (ByteArrayOutputStream baos = new ByteArrayOutputStream();
+ DataOutputStream out = new DataOutputViewStreamWrapper(baos)) {
+
+ out.writeLong(this.inFlightCheckpoint);
+ byte[] serializedInstant = this.inFlightInstant.getBytes();
+ out.writeInt(serializedInstant.length);
+ out.write(serializedInstant);
+ out.flush();
+ return baos.toByteArray();
+ }
+ }
+
+ /**
+ * Restore the state of this source coordinator from the state bytes.
+ *
+ * @param bytes The checkpoint bytes that was returned from {@link
#writeCheckpointBytes()}
+ * @throws Exception When the deserialization failed.
+ */
+ private void deserializeCheckpointAndRestore(byte[] bytes) throws Exception {
+ try (ByteArrayInputStream bais = new ByteArrayInputStream(bytes);
+ DataInputStream in = new DataInputViewStreamWrapper(bais)) {
+ long checkpointID = in.readLong();
+ int serializedInstantSize = in.readInt();
+ byte[] serializedInstant = readBytes(in, serializedInstantSize);
+ this.inFlightCheckpoint = checkpointID;
+ this.inFlightInstant = new String(serializedInstant);
+ }
+ }
+
+ private void reset() {
+ this.inFlightInstant = "";
+ this.eventBuffer = new BatchWriteSuccessEvent[this.parallelism];
+ }
+
+ private void checkAndForceCommit(String errMsg) {
+ if (!checkReady()) {
+ // forced but still has inflight instant
+ String inflightInstant =
writeClient.getInflightAndRequestedInstant(this.conf.getString(FlinkOptions.TABLE_TYPE));
+ if (inflightInstant != null) {
+ assert inflightInstant.equals(this.inFlightInstant);
+ writeClient.rollback(this.inFlightInstant);
+ throw new HoodieException(errMsg);
+ }
+ if (Arrays.stream(eventBuffer).allMatch(Objects::isNull)) {
+ // The last checkpoint finished successfully.
+ return;
+ }
+ }
+ doCommit();
+ }
+
+ private void checkAndCommitWithRetry() {
+ int retryTimes = this.conf.getInteger(FlinkOptions.RETRY_TIMES);
+ long retryIntervalMillis =
this.conf.getLong(FlinkOptions.RETRY_INTERVAL_MS);
+ int tryTimes = 0;
+ while (tryTimes++ < retryTimes) {
+ try {
+ if (!checkReady()) {
+ // Do not throw if the try times expires but the event buffer are
still not ready,
+ // because we have a force check when next checkpoint starts.
+ waitFor(retryIntervalMillis);
+ continue;
+ }
+ doCommit();
+ return;
+ } catch (Throwable throwable) {
+ String cause = throwable.getCause() == null ? "" :
throwable.getCause().toString();
+ LOG.warn("Try to commit the instant {} failed, with times {} and cause
{}", this.inFlightInstant, tryTimes, cause);
+ if (tryTimes == retryTimes) {
+ throw new HoodieException(throwable);
+ }
+ waitFor(retryIntervalMillis);
+ }
+ }
+ }
+
+ private void waitFor(long intervalMillis) {
+ try {
+ TimeUnit.MILLISECONDS.sleep(intervalMillis);
+ } catch (InterruptedException e) {
+ LOG.error("Thread interrupted while waiting to retry the instant
commits");
+ throw new HoodieException(e);
+ }
+ }
+
+ /** Checks the buffer is ready to commit. */
+ private boolean checkReady() {
+ return Arrays.stream(eventBuffer).allMatch(event ->
+ event != null && event.getInstantTime().equals(this.inFlightInstant));
+ }
+
+ /** Performs the actual commit action. */
+ private void doCommit() {
+ List<WriteStatus> writeResults = Arrays.stream(eventBuffer)
+ .map(BatchWriteSuccessEvent::getWriteStatuses)
+ .flatMap(Collection::stream)
+ .collect(Collectors.toList());
+
+ if (writeResults.size() == 0) {
+ // No data has written, clear the metadata file
+
this.writeClient.deletePendingInstant(this.conf.getString(FlinkOptions.TABLE_TYPE),
this.inFlightInstant);
+ reset();
+ return;
+ }
+
+ // commit or rollback
+ long totalErrorRecords =
writeResults.stream().map(WriteStatus::getTotalErrorRecords).reduce(Long::sum).orElse(0L);
+ long totalRecords =
writeResults.stream().map(WriteStatus::getTotalRecords).reduce(Long::sum).orElse(0L);
+ boolean hasErrors = totalErrorRecords > 0;
+
+ if (!hasErrors || this.conf.getBoolean(FlinkOptions.IGNORE_FAILED_BATCH)) {
+ HashMap<String, String> checkpointCommitMetadata = new HashMap<>();
+ if (hasErrors) {
+ LOG.warn("Some records failed to merge but forcing commit since
commitOnErrors set to true. Errors/Total="
+ + totalErrorRecords + "/" + totalRecords);
+ }
+
+ boolean success = writeClient.commit(this.inFlightInstant, writeResults,
Option.of(checkpointCommitMetadata));
+ if (success) {
+ reset();
+ LOG.info("Commit instant [{}] success!", this.inFlightInstant);
+ } else {
+ throw new HoodieException(String.format("Commit instant [%s] failed!",
this.inFlightInstant));
+ }
+ } else {
+ LOG.error("Error when writing. Errors/Total=" + totalErrorRecords + "/"
+ totalRecords);
+ LOG.error("The first 100 error messages");
+
writeResults.stream().filter(WriteStatus::hasErrors).limit(100).forEach(ws -> {
+ LOG.error("Global error for partition path {} and fileID {}: {}",
+ ws.getGlobalError(), ws.getPartitionPath(), ws.getFileId());
+ if (ws.getErrors().size() > 0) {
+ ws.getErrors().forEach((key, value) -> LOG.trace("Error for key:" +
key + " and value " + value));
+ }
+ });
+ // Rolls back instant
+ writeClient.rollback(this.inFlightInstant);
+ throw new HoodieException(String.format("Commit instant [%s] failed and
rolled back !", this.inFlightInstant));
+ }
+ }
+
+ @VisibleForTesting
+ public BatchWriteSuccessEvent[] getEventBuffer() {
+ return eventBuffer;
+ }
+
+ @VisibleForTesting
+ public String getInFlightInstant() {
Review comment:
is this only visible for testing? IIUC, the actual writer need to know
the current instant and add `_hoodie_commit_time` field to the record. How did
the writer know the current instant?
##########
File path:
hudi-flink/src/main/java/org/apache/hudi/operator/StreamWriteFunction.java
##########
@@ -0,0 +1,342 @@
+/*
+ * 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.hudi.operator;
+
+import org.apache.hudi.avro.HoodieAvroUtils;
+import org.apache.hudi.client.FlinkTaskContextSupplier;
+import org.apache.hudi.client.HoodieFlinkWriteClient;
+import org.apache.hudi.client.WriteStatus;
+import org.apache.hudi.client.common.HoodieFlinkEngineContext;
+import org.apache.hudi.common.config.SerializableConfiguration;
+import org.apache.hudi.common.model.HoodieRecord;
+import org.apache.hudi.common.model.HoodieRecordPayload;
+import org.apache.hudi.common.model.WriteOperationType;
+import org.apache.hudi.common.util.ObjectSizeCalculator;
+import org.apache.hudi.keygen.KeyGenerator;
+import org.apache.hudi.operator.event.BatchWriteSuccessEvent;
+import org.apache.hudi.util.StreamerUtil;
+
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.flink.annotation.VisibleForTesting;
+import org.apache.flink.configuration.Configuration;
+import org.apache.flink.formats.avro.RowDataToAvroConverters;
+import org.apache.flink.runtime.operators.coordination.OperatorEventGateway;
+import org.apache.flink.runtime.state.FunctionInitializationContext;
+import org.apache.flink.runtime.state.FunctionSnapshotContext;
+import org.apache.flink.streaming.api.checkpoint.CheckpointedFunction;
+import org.apache.flink.streaming.api.functions.KeyedProcessFunction;
+import org.apache.flink.table.types.logical.RowType;
+import org.apache.flink.util.Collector;
+import org.apache.flink.util.Preconditions;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.Collections;
+import java.util.List;
+import java.util.Random;
+import java.util.concurrent.locks.Condition;
+import java.util.concurrent.locks.ReentrantLock;
+import java.util.function.BiFunction;
+
+/**
+ * Sink function to write the data to the underneath filesystem.
+ *
+ * <p><h2>Work Flow</h2>
+ *
+ * <p>The function firstly buffers the data as a batch of {@link
HoodieRecord}s,
+ * It flushes(write) the records batch when a Flink checkpoint starts. After a
batch has been written successfully,
+ * the function notifies its operator coordinator {@link
StreamWriteOperatorCoordinator} to mark a successful write.
+ *
+ * <p><h2>Exactly-once Semantics</h2>
+ *
+ * <p>The task implements exactly-once semantics by buffering the data between
checkpoints. The operator coordinator
+ * starts a new instant on the time line when a checkpoint triggers, the
coordinator checkpoints always
+ * start before its operator, so when this function starts a checkpoint, a
REQUESTED instant already exists.
+ * The function process thread then block data buffering and the checkpoint
thread starts flushing the existing data buffer.
+ * When the existing data buffer write successfully, the process thread
unblock and start buffering again for the next round checkpoint.
+ * Because any checkpoint failures would trigger the write rollback, it
implements the exactly-once semantics.
+ *
+ * <p><h2>Fault Tolerance</h2>
+ *
+ * <p>The operator coordinator checks the validity for the last instant when
it starts a new one. The operator rolls back
+ * the written data and throws when any error occurs. This means any
checkpoint or task failure would trigger a failover.
+ * The operator coordinator would try several times when committing the
writestatus.
+ *
+ * <p>Note: The function task requires the input stream be partitioned by the
partition fields to avoid different write tasks
+ * write to the same file group that conflict. The general case for partition
path is a datetime field,
+ * so the sink task is very possible to have IO bottleneck, the more flexible
solution is to shuffle the
+ * data by the file group IDs.
+ *
+ * @param <I> Type of the input record
+ * @see StreamWriteOperatorCoordinator
+ */
+public class StreamWriteFunction<K, I, O>
+ extends KeyedProcessFunction<K, I, O>
+ implements CheckpointedFunction {
+
+ private static final long serialVersionUID = 1L;
+
+ private static final Logger LOG =
LoggerFactory.getLogger(StreamWriteFunction.class);
+
+ /**
+ * Write buffer for a checkpoint.
+ */
+ private transient List<HoodieRecord> buffer;
+
+ /**
+ * The buffer lock to control data buffering/flushing.
+ */
+ private transient ReentrantLock bufferLock;
+
+ /**
+ * The condition to decide whether to add new records into the buffer.
+ */
+ private transient Condition addToBufferCondition;
+
+ /**
+ * Flag saying whether there is an on-going checkpoint.
+ */
+ private volatile boolean onCheckpointing = false;
+
+ /**
+ * Config options.
+ */
+ private final Configuration config;
+
+ /**
+ * Id of current subtask.
+ */
+ private int taskID;
+
+ /**
+ * Write Client.
+ */
+ private transient HoodieFlinkWriteClient writeClient;
+
+ private transient BiFunction<List<HoodieRecord>, String, List<WriteStatus>>
writeFunction;
+
+ /**
+ * HoodieKey generator.
+ */
+ private transient KeyGenerator keyGenerator;
+
+ /**
+ * Row type of the input.
+ */
+ private final RowType rowType;
+
+ /**
+ * Avro schema of the input.
+ */
+ private final Schema avroSchema;
+
+ private transient RowDataToAvroConverters.RowDataToAvroConverter converter;
+
+ /**
+ * The REQUESTED instant we write the data.
+ */
+ private volatile String currentInstant;
+
+ /**
+ * Gateway to send operator events to the operator coordinator.
+ */
+ private transient OperatorEventGateway eventGateway;
+
+ /**
+ * Constructs a StreamingSinkFunction.
+ *
+ * @param rowType The input row type
+ * @param config The config options
+ */
+ public StreamWriteFunction(RowType rowType, Configuration config) {
+ this.rowType = rowType;
+ this.avroSchema = org.apache.flink.formats.avro.typeutils
+ .AvroSchemaConverter.convertToSchema(rowType);
+ this.config = config;
+ }
+
+ @Override
+ public void open(Configuration parameters) throws IOException {
+ this.taskID = getRuntimeContext().getIndexOfThisSubtask();
+ this.keyGenerator =
StreamerUtil.createKeyGenerator(HoodieOptions.flatOptions(this.config));
+ this.converter = RowDataToAvroConverters.createConverter(this.rowType);
+ initBuffer();
+ initWriteClient();
+ initWriteFunction();
+ }
+
+ @Override
+ public void initializeState(FunctionInitializationContext context) {
+ // no operation
+ }
+
+ @Override
+ public void snapshotState(FunctionSnapshotContext functionSnapshotContext) {
+ bufferLock.lock();
+ try {
+ // Based on the fact that the coordinator starts the checkpoint first,
+ // it would check the validity.
+ this.onCheckpointing = true;
+ this.currentInstant =
this.writeClient.getInflightAndRequestedInstant(this.config.get(HoodieOptions.TABLE_TYPE));
+ Preconditions.checkNotNull(this.currentInstant,
+ "No inflight instant when flushing data");
+ // wait for the buffer data flush out and request a new instant
+ flushBuffer();
+ // signal the task thread to start buffering
+ addToBufferCondition.signal();
+ } finally {
+ this.onCheckpointing = false;
+ bufferLock.unlock();
+ }
+ }
+
+ @Override
+ public void processElement(I value, KeyedProcessFunction<K, I, O>.Context
ctx, Collector<O> out) throws Exception {
+ bufferLock.lock();
+ try {
+ if (onCheckpointing) {
+ addToBufferCondition.await();
+ }
+ this.buffer.add(toHoodie(value));
+ } finally {
+ bufferLock.unlock();
+ }
+ }
+
+ @Override
+ public void close() {
+ if (this.writeClient != null) {
+ this.writeClient.close();
+ }
+ }
+
+ // -------------------------------------------------------------------------
+ // Getter/Setter
+ // -------------------------------------------------------------------------
+
+ @VisibleForTesting
+ @SuppressWarnings("rawtypes")
+ public List<HoodieRecord> getBuffer() {
+ return buffer;
+ }
+
+ @VisibleForTesting
+ @SuppressWarnings("rawtypes")
+ public HoodieFlinkWriteClient getWriteClient() {
+ return writeClient;
+ }
+
+ public void setOperatorEventGateway(OperatorEventGateway
operatorEventGateway) {
+ this.eventGateway = operatorEventGateway;
+ }
+
+ // -------------------------------------------------------------------------
+ // Utilities
+ // -------------------------------------------------------------------------
+
+ private void initBuffer() {
+ this.buffer = new ArrayList<>();
+ this.bufferLock = new ReentrantLock();
+ this.addToBufferCondition = this.bufferLock.newCondition();
+ }
+
+ private void initWriteClient() {
+ HoodieFlinkEngineContext context =
+ new HoodieFlinkEngineContext(
+ new SerializableConfiguration(StreamerUtil.getHadoopConf()),
+ new FlinkTaskContextSupplier(getRuntimeContext()));
+
+ writeClient = new HoodieFlinkWriteClient<>(context,
StreamerUtil.getHoodieClientConfig(this.config));
+ }
+
+ private void initWriteFunction() {
+ final String writeOperation = this.config.get(HoodieOptions.OPERATION);
+ switch (WriteOperationType.fromValue(writeOperation)) {
+ case INSERT:
+ this.writeFunction = (records, instantTime) ->
this.writeClient.insert(records, instantTime);
+ break;
+ case UPSERT:
+ this.writeFunction = (records, instantTime) ->
this.writeClient.upsert(records, instantTime);
+ break;
+ default:
+ throw new RuntimeException("Unsupported write operation : " +
writeOperation);
+ }
+ }
+
+ // Keep for mini-batch write.
+ private static class BufferSizeEstimator {
Review comment:
Can we add some docs here. Still a little bit confused about how this
will be used.
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