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Posted to user-zh@flink.apache.org by 夏帅 <jk...@dingtalk.com.INVALID> on 2020/06/28 10:27:03 UTC
回复：flink1.10 使用 ParquetAvroWriters schema 模式写数据问题
你好,这个问题从异常来看是使用TupleTypeInfo导致的,可以试下使用GenericRecordAvroTypeInfo
------------------------------------------------------------------
发件人：yingbo yang <ya...@gmail.com>
发送时间：2020年6月28日(星期日) 17:38
收件人：user-zh <us...@flink.apache.org>
主 题：flink1.10 使用 ParquetAvroWriters schema 模式写数据问题
Hi：
在使用 ParquetAvroWriters.forGenericRecord(Schema schema)
写parquet文件的时候 出现 类转化异常：
下面是我的代码：
// //transfor 2 dataStream // TupleTypeInfo tupleTypeInfo = new
TupleTypeInfo(GenericData.Record.class,
BasicTypeInfo.STRING_TYPE_INFO, BasicTypeInfo.STRING_TYPE_INFO);
TupleTypeInfo tupleTypeInfo = new
TupleTypeInfo(BasicTypeInfo.STRING_TYPE_INFO,
BasicTypeInfo.STRING_TYPE_INFO);
DataStream testDataStream = flinkTableEnv.toAppendStream(test, tupleTypeInfo);
testDataStream.print().setParallelism(1);
ArrayList<org.apache.avro.Schema.Field> fields = new
ArrayList<org.apache.avro.Schema.Field>();
fields.add(new org.apache.avro.Schema.Field("id",
org.apache.avro.Schema.create(org.apache.avro.Schema.Type.STRING),
"id", JsonProperties.NULL_VALUE));
fields.add(new org.apache.avro.Schema.Field("time",
org.apache.avro.Schema.create(org.apache.avro.Schema.Type.STRING),
"time", JsonProperties.NULL_VALUE));
org.apache.avro.Schema parquetSinkSchema =
org.apache.avro.Schema.createRecord("pi", "flinkParquetSink",
"flink.parquet", true, fields);
String fileSinkPath = "./xxx.text/rs6/";
StreamingFileSink<GenericRecord> parquetSink = StreamingFileSink.
forBulkFormat(new Path(fileSinkPath),
ParquetAvroWriters.forGenericRecord(parquetSinkSchema))
.withRollingPolicy(OnCheckpointRollingPolicy.build())
.build();
testDataStream.addSink(parquetSink).setParallelism(1);
flinkTableEnv.execute("ReadFromKafkaConnectorWriteToLocalFileJava");
下面是异常：
09:29:50,283 INFO org.apache.flink.runtime.taskmanager.Task
- Sink: Unnamed (1/1) (79505cb6ab2df38886663fd99461315a)
switched from RUNNING to FAILED.09:29:50,283 INFO
org.apache.flink.runtime.taskmanager.Task - Sink:
Unnamed (1/1) (79505cb6ab2df38886663fd99461315a) switched from RUNNING
to FAILED.java.lang.ClassCastException:
org.apache.flink.api.java.tuple.Tuple2 cannot be cast to
org.apache.avro.generic.IndexedRecord
at org.apache.avro.generic.GenericData.getField(GenericData.java:697)
at org.apache.parquet.avro.AvroWriteSupport.writeRecordFields(AvroWriteSupport.java:188)
at org.apache.parquet.avro.AvroWriteSupport.write(AvroWriteSupport.java:165)
at org.apache.parquet.hadoop.InternalParquetRecordWriter.write(InternalParquetRecordWriter.java:128)
at org.apache.parquet.hadoop.ParquetWriter.write(ParquetWriter.java:299)
at org.apache.flink.formats.parquet.ParquetBulkWriter.addElement(ParquetBulkWriter.java:52)
at org.apache.flink.streaming.api.functions.sink.filesystem.BulkPartWriter.write(BulkPartWriter.java:50)
at org.apache.flink.streaming.api.functions.sink.filesystem.Bucket.write(Bucket.java:214)
at org.apache.flink.streaming.api.functions.sink.filesystem.Buckets.onElement(Buckets.java:274)
at org.apache.flink.streaming.api.functions.sink.filesystem.StreamingFileSink.invoke(StreamingFileSink.java:445)
at org.apache.flink.streaming.api.operators.StreamSink.processElement(StreamSink.java:56)
at org.apache.flink.streaming.runtime.tasks.OneInputStreamTask$StreamTaskNetworkOutput.emitRecord(OneInputStreamTask.java:173)
at org.apache.flink.streaming.runtime.io.StreamTaskNetworkInput.processElement(StreamTaskNetworkInput.java:151)
at org.apache.flink.streaming.runtime.io.StreamTaskNetworkInput.emitNext(StreamTaskNetworkInput.java:128)
at org.apache.flink.streaming.runtime.io.StreamOneInputProcessor.processInput(StreamOneInputProcessor.java:69)
at org.apache.flink.streaming.runtime.tasks.StreamTask.processInput(StreamTask.java:311)
at org.apache.flink.streaming.runtime.tasks.mailbox.MailboxProcessor.runMailboxLoop(MailboxProcessor.java:187)
at org.apache.flink.streaming.runtime.tasks.StreamTask.runMailboxLoop(StreamTask.java:487)
at org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:470)
at org.apache.flink.runtime.taskmanager.Task.doRun(Task.java:707)
at org.apache.flink.runtime.taskmanager.Task.run(Task.java:532)
at java.lang.Thread.run(Thread.java:748)09:29:50,284
INFO org.apache.flink.runtime.taskmanager.Task -
Freeing task resources for Sink: Unnamed (1/1)
(79505cb6ab2df38886663fd99461315a).09:29:50,285 INFO
org.apache.flink.runtime.taskmanager.Task -
Ensuring all FileSystem streams are closed for task Sink: Unnamed
(1/1) (79505cb6ab2df38886663fd99461315a) [FAILED]09:29:50,289
INFO org.apache.flink.runtime.taskexecutor.TaskExecutor -
Un-registering task and sending final execution state FAILED to
JobManager for task Sink: Unnamed (1/1)
79505cb6ab2df38886663fd99461315a.09:29:50,293 INFO
org.apache.flink.runtime.executiongraph.ExecutionGraph - Sink:
Unnamed (1/1) (79505cb6ab2df38886663fd99461315a)
switched from RUNNING to FAILED.java.lang.ClassCastException:
org.apache.flink.api.java.tuple.Tuple2 cannot be cast to
org.apache.avro.generic.IndexedRecord at
org.apache.avro.generic.GenericData.getField(GenericData.java:697) at
org.apache.parquet.avro.AvroWriteSupport.writeRecordFields(AvroWriteSupport.java:188)
at org.apache.parquet.avro.AvroWriteSupport.write(AvroWriteSupport.java:165)
请问是否是使用方式不对？还是什么问题？
回复：flink1.10 使用 ParquetAvroWriters schema 模式写数据问题
Posted by 夏帅 <jk...@dingtalk.com.INVALID>.
你好,我试了一下,纯DataStream的方式是可以使用的,具体使用参考`flink-formats\flink-parquet\src\test\java\org\apache\flink\formats\parquet\avro\ParquetStreamingFileSinkITCase`
在Table转DataStream的方式中,我是先将Table转换为DataStream[Row],然后再进行转换生成DataStream[GenericRecord]
dataStream.map(x => {
...val fields = new util.ArrayList[Schema.Field]
fields.add(new Schema.Field("platform", create(org.apache.avro.Schema.Type.STRING), "platform", null))
fields.add(new Schema.Field("event", create(org.apache.avro.Schema.Type.STRING), "event", null))
fields.add(new Schema.Field("dt", create(org.apache.avro.Schema.Type.STRING), "dt", null))
val parquetSinkSchema: Schema = createRecord("pi", "flinkParquetSink",
"flink.parquet", true, fields)
val record = new GenericData.Record(parquetSinkSchema).asInstanceOf[GenericRecord]
record.put("platform", x.get(0))
record.put("event", x.get(1))
record.put("dt", x.get(2))
record
})
------------------------------------------------------------------
发件人：yingbo yang <ya...@gmail.com>
发送时间：2020年6月29日(星期一) 10:04
收件人：夏帅 <jk...@dingtalk.com>
抄 送：user-zh <us...@flink.apache.org>
主 题：Re: flink1.10 使用 ParquetAvroWriters schema 模式写数据问题
你好：
可以使用 GenericRecordAvroTypeInfo 这个类型，但是这个类型只适合于 table 中只有一个 字段的情况；否则会出现异常：
代码：
ArrayList<org.apache.avro.Schema.Field> fields = new ArrayList<org.apache.avro.Schema.Field>();
fields.add(new org.apache.avro.Schema.Field("id", org.apache.avro.Schema.create(org.apache.avro.Schema.Type.STRING), "id", JsonProperties.NULL_VALUE));
fields.add(new org.apache.avro.Schema.Field("time", org.apache.avro.Schema.create(org.apache.avro.Schema.Type.STRING), "time", JsonProperties.NULL_VALUE));
org.apache.avro.Schema parquetSinkSchema = org.apache.avro.Schema.createRecord("pi", "flinkParquetSink", "flink.parquet", true, fields);
String fileSinkPath = "./xxx.text/rs6/";
GenericRecordAvroTypeInfo genericRecordAvroTypeInfo = new GenericRecordAvroTypeInfo(parquetSinkSchema);
DataStream testDataStream1 = flinkTableEnv.toAppendStream(test, genericRecordAvroTypeInfo);
testDataStream1.print().setParallelism(1);
StreamingFileSink<GenericRecord> parquetSink = StreamingFileSink.
forBulkFormat(new Path(fileSinkPath),
ParquetAvroWriters.forGenericRecord(parquetSinkSchema))
.withRollingPolicy(OnCheckpointRollingPolicy.build())
.build();
testDataStream1.addSink(parquetSink).setParallelism(1);
flinkTableEnv.execute("ReadFromKafkaConnectorWriteToLocalFileJava");
异常：
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/Users/yyb/Software/localRepository/org/slf4j/slf4j-log4j12/1.7.7/slf4j-log4j12-1.7.7.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/Users/yyb/Software/localRepository/org/apache/logging/log4j/log4j-slf4j-impl/2.6.2/log4j-slf4j-impl-2.6.2.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
root
|-- id: STRING
|-- time: STRING
09:40:35,872 INFO org.apache.flink.api.java.typeutils.TypeExtractor - class org.apache.flink.types.Row does not contain a getter for field fields
09:40:35,874 INFO org.apache.flink.api.java.typeutils.TypeExtractor - class org.apache.flink.types.Row does not contain a setter for field fields
09:40:35,874 INFO org.apache.flink.api.java.typeutils.TypeExtractor - Class class org.apache.flink.types.Row cannot be used as a POJO type because not all fields are valid POJO fields, and must be processed as GenericType. Please read the Flink documentation on "Data Types & Serialization" for details of the effect on performance.
09:40:36,191 INFO org.apache.flink.api.java.typeutils.TypeExtractor - class org.apache.flink.types.Row does not contain a getter for field fields
09:40:36,191 INFO org.apache.flink.api.java.typeutils.TypeExtractor - class org.apache.flink.types.Row does not contain a setter for field fields
09:40:36,191 INFO org.apache.flink.api.java.typeutils.TypeExtractor - Class class org.apache.flink.types.Row cannot be used as a POJO type because not all fields are valid POJO fields, and must be processed as GenericType. Please read the Flink documentation on "Data Types & Serialization" for details of the effect on performance.
Exception in thread "main" org.apache.flink.table.api.TableException: Arity [2] of result [[Lorg.apache.flink.api.common.typeinfo.TypeInformation;@2149594a] does not match the number[1] of requested type [GenericRecord("{"type":"error","name":"pi","namespace":"flink.parquet","doc":"flinkParquetSink","fields":[{"name":"id","type":"string","doc":"id","default":null},{"name":"time","type":"string","doc":"time","default":null}]}")].
at org.apache.flink.table.planner.Conversions$.generateRowConverterFunction(Conversions.scala:66)
at org.apache.flink.table.planner.DataStreamConversions$.getConversionMapper(DataStreamConversions.scala:135)
at org.apache.flink.table.planner.DataStreamConversions$.convert(DataStreamConversions.scala:91)
at org.apache.flink.table.planner.StreamPlanner.translateOptimized(StreamPlanner.scala:413)
at org.apache.flink.table.planner.StreamPlanner.translateToType(StreamPlanner.scala:402)
at org.apache.flink.table.planner.StreamPlanner.org$apache$flink$table$planner$StreamPlanner$$translate(StreamPlanner.scala:180)
at org.apache.flink.table.planner.StreamPlanner$$anonfun$translate$1.apply(StreamPlanner.scala:117)
at org.apache.flink.table.planner.StreamPlanner$$anonfun$translate$1.apply(StreamPlanner.scala:117)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
at scala.collection.AbstractTraversable.map(Traversable.scala:104)
at org.apache.flink.table.planner.StreamPlanner.translate(StreamPlanner.scala:117)
at org.apache.flink.table.api.java.internal.StreamTableEnvironmentImpl.toDataStream(StreamTableEnvironmentImpl.java:351)
at org.apache.flink.table.api.java.internal.StreamTableEnvironmentImpl.toAppendStream(StreamTableEnvironmentImpl.java:259)
at com.yyb.flink10.table.blink.stream.FileSystem.ReadFromKafkaConnectorWriteToLocalParquetFileJava.main(ReadFromKafkaConnectorWriteToLocalParquetFileJava.java:96)
Process finished with exit code 1
夏帅 <jk...@dingtalk.com> 于2020年6月28日周日 下午6:27写道：
你好,这个问题从异常来看是使用TupleTypeInfo导致的,可以试下使用GenericRecordAvroTypeInfo
------------------------------------------------------------------
发件人：yingbo yang <ya...@gmail.com>
发送时间：2020年6月28日(星期日) 17:38
收件人：user-zh <us...@flink.apache.org>
主 题：flink1.10 使用 ParquetAvroWriters schema 模式写数据问题
Hi：
在使用 ParquetAvroWriters.forGenericRecord(Schema schema)
写parquet文件的时候 出现 类转化异常：
下面是我的代码：
// //transfor 2 dataStream // TupleTypeInfo tupleTypeInfo = new
TupleTypeInfo(GenericData.Record.class,
BasicTypeInfo.STRING_TYPE_INFO, BasicTypeInfo.STRING_TYPE_INFO);
TupleTypeInfo tupleTypeInfo = new
TupleTypeInfo(BasicTypeInfo.STRING_TYPE_INFO,
BasicTypeInfo.STRING_TYPE_INFO);
DataStream testDataStream = flinkTableEnv.toAppendStream(test, tupleTypeInfo);
testDataStream.print().setParallelism(1);
ArrayList<org.apache.avro.Schema.Field> fields = new
ArrayList<org.apache.avro.Schema.Field>();
fields.add(new org.apache.avro.Schema.Field("id",
org.apache.avro.Schema.create(org.apache.avro.Schema.Type.STRING),
"id", JsonProperties.NULL_VALUE));
fields.add(new org.apache.avro.Schema.Field("time",
org.apache.avro.Schema.create(org.apache.avro.Schema.Type.STRING),
"time", JsonProperties.NULL_VALUE));
org.apache.avro.Schema parquetSinkSchema =
org.apache.avro.Schema.createRecord("pi", "flinkParquetSink",
"flink.parquet", true, fields);
String fileSinkPath = "./xxx.text/rs6/";
StreamingFileSink<GenericRecord> parquetSink = StreamingFileSink.
forBulkFormat(new Path(fileSinkPath),
ParquetAvroWriters.forGenericRecord(parquetSinkSchema))
.withRollingPolicy(OnCheckpointRollingPolicy.build())
.build();
testDataStream.addSink(parquetSink).setParallelism(1);
flinkTableEnv.execute("ReadFromKafkaConnectorWriteToLocalFileJava");
下面是异常：
09:29:50,283 INFO org.apache.flink.runtime.taskmanager.Task
- Sink: Unnamed (1/1) (79505cb6ab2df38886663fd99461315a)
switched from RUNNING to FAILED.09:29:50,283 INFO
org.apache.flink.runtime.taskmanager.Task - Sink:
Unnamed (1/1) (79505cb6ab2df38886663fd99461315a) switched from RUNNING
to FAILED.java.lang.ClassCastException:
org.apache.flink.api.java.tuple.Tuple2 cannot be cast to
org.apache.avro.generic.IndexedRecord
at org.apache.avro.generic.GenericData.getField(GenericData.java:697)
at org.apache.parquet.avro.AvroWriteSupport.writeRecordFields(AvroWriteSupport.java:188)
at org.apache.parquet.avro.AvroWriteSupport.write(AvroWriteSupport.java:165)
at org.apache.parquet.hadoop.InternalParquetRecordWriter.write(InternalParquetRecordWriter.java:128)
at org.apache.parquet.hadoop.ParquetWriter.write(ParquetWriter.java:299)
at org.apache.flink.formats.parquet.ParquetBulkWriter.addElement(ParquetBulkWriter.java:52)
at org.apache.flink.streaming.api.functions.sink.filesystem.BulkPartWriter.write(BulkPartWriter.java:50)
at org.apache.flink.streaming.api.functions.sink.filesystem.Bucket.write(Bucket.java:214)
at org.apache.flink.streaming.api.functions.sink.filesystem.Buckets.onElement(Buckets.java:274)
at org.apache.flink.streaming.api.functions.sink.filesystem.StreamingFileSink.invoke(StreamingFileSink.java:445)
at org.apache.flink.streaming.api.operators.StreamSink.processElement(StreamSink.java:56)
at org.apache.flink.streaming.runtime.tasks.OneInputStreamTask$StreamTaskNetworkOutput.emitRecord(OneInputStreamTask.java:173)
at org.apache.flink.streaming.runtime.io.StreamTaskNetworkInput.processElement(StreamTaskNetworkInput.java:151)
at org.apache.flink.streaming.runtime.io.StreamTaskNetworkInput.emitNext(StreamTaskNetworkInput.java:128)
at org.apache.flink.streaming.runtime.io.StreamOneInputProcessor.processInput(StreamOneInputProcessor.java:69)
at org.apache.flink.streaming.runtime.tasks.StreamTask.processInput(StreamTask.java:311)
at org.apache.flink.streaming.runtime.tasks.mailbox.MailboxProcessor.runMailboxLoop(MailboxProcessor.java:187)
at org.apache.flink.streaming.runtime.tasks.StreamTask.runMailboxLoop(StreamTask.java:487)
at org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:470)
at org.apache.flink.runtime.taskmanager.Task.doRun(Task.java:707)
at org.apache.flink.runtime.taskmanager.Task.run(Task.java:532)
at java.lang.Thread.run(Thread.java:748)09:29:50,284
INFO org.apache.flink.runtime.taskmanager.Task -
Freeing task resources for Sink: Unnamed (1/1)
(79505cb6ab2df38886663fd99461315a).09:29:50,285 INFO
org.apache.flink.runtime.taskmanager.Task -
Ensuring all FileSystem streams are closed for task Sink: Unnamed
(1/1) (79505cb6ab2df38886663fd99461315a) [FAILED]09:29:50,289
INFO org.apache.flink.runtime.taskexecutor.TaskExecutor -
Un-registering task and sending final execution state FAILED to
JobManager for task Sink: Unnamed (1/1)
79505cb6ab2df38886663fd99461315a.09:29:50,293 INFO
org.apache.flink.runtime.executiongraph.ExecutionGraph - Sink:
Unnamed (1/1) (79505cb6ab2df38886663fd99461315a)
switched from RUNNING to FAILED.java.lang.ClassCastException:
org.apache.flink.api.java.tuple.Tuple2 cannot be cast to
org.apache.avro.generic.IndexedRecord at
org.apache.avro.generic.GenericData.getField(GenericData.java:697) at
org.apache.parquet.avro.AvroWriteSupport.writeRecordFields(AvroWriteSupport.java:188)
at org.apache.parquet.avro.AvroWriteSupport.write(AvroWriteSupport.java:165)
请问是否是使用方式不对？还是什么问题？