mahesh2247 commented on issue #7688:
URL: https://github.com/apache/hudi/issues/7688#issuecomment-1387103851
Error as on 7:16pm IST for the below code -
Literally able to run this script for insert and update without the
```deleteConfig = {'hoodie.datasource.write.operation': 'delete',
'hoodie.delete.shuffle.parallelism': '1'}```
CODE -
```
import sys
from awsglue.transforms import *
from awsglue.utils import getResolvedOptions
from pyspark.sql.session import SparkSession
from pyspark.context import SparkContext
from awsglue.context import GlueContext
from awsglue.job import Job
from pyspark.sql import DataFrame, Row
from pyspark.sql.functions import *
from pyspark.sql.functions import col, to_timestamp,
monotonically_increasing_id, to_date, when
import datetime
from pyspark.sql import functions as F
from awsglue import DynamicFrame
import boto3
## @params: [JOB_NAME]
args = getResolvedOptions(sys.argv, ["JOB_NAME", "database_name",
"kinesis_table_name", "starting_position_of_kinesis_iterator",
"hudi_table_name", "window_size", "s3_path_hudi", "s3_path_spark" ])
spark =
SparkSession.builder.config('spark.serializer','org.apache.spark.serializer.KryoSerializer').config('spark.sql.hive.convertMetastoreParquet','false').getOrCreate()
sc = spark.sparkContext
glueContext = GlueContext(sc)
job = Job(glueContext)
job.init(args['JOB_NAME'], args)
database_name = args["database_name"]
kinesis_table_name = args["kinesis_table_name"]
hudi_table_name = args["hudi_table_name"]
s3_path_hudi = args["s3_path_hudi"]
s3_path_spark = args["s3_path_spark"]
commonConfig = {'hoodie.datasource.write.hive_style_partitioning' :
'true','className' : 'org.apache.hudi',
'hoodie.datasource.hive_sync.use_jdbc':'false',
'hoodie.datasource.write.precombine.field': 'id',
'hoodie.datasource.write.recordkey.field': 'id', 'hoodie.table.name':
hudi_table_name, 'hoodie.consistency.check.enabled': 'true',
'hoodie.datasource.hive_sync.database': database_name,
'hoodie.datasource.hive_sync.table': hudi_table_name,
'hoodie.datasource.hive_sync.enable': 'true', 'path': s3_path_hudi}
partitionDataConfig = { 'hoodie.datasource.write.keygenerator.class' :
'org.apache.hudi.keygen.ComplexKeyGenerator',
'hoodie.datasource.write.partitionpath.field': "partitionkey, partitionkey2 ",
'hoodie.datasource.hive_sync.partition_extractor_class':
'org.apache.hudi.hive.MultiPartKeysValueExtractor',
'hoodie.datasource.hive_sync.partition_fields': "partitionkey, partitionkey2"}
incrementalConfig = {'hoodie.upsert.shuffle.parallelism': 68,
'hoodie.datasource.write.operation': 'upsert', 'hoodie.cleaner.policy':
'KEEP_LATEST_COMMITS', 'hoodie.cleaner.commits.retained': 2}
deleteConfig = {'hoodie.datasource.write.operation': 'delete',
'hoodie.delete.shuffle.parallelism': '1'}
combinedConf = {**commonConfig, **partitionDataConfig, **incrementalConfig,
**deleteConfig}
glue_temp_storage = s3_path_hudi
data_frame_DataSource0 = glueContext.create_data_frame.from_catalog(database
= database_name, table_name = kinesis_table_name, transformation_ctx =
"DataSource0", additional_options = {"startingPosition": "TRIM_HORIZON",
"inferSchema": "true"})
def processBatch(data_frame, batchId):
if (data_frame.count() > 0):
DataSource0 = DynamicFrame.fromDF(data_frame, glueContext,
"from_data_frame")
your_map = [
('eventName', 'string', 'eventName', 'string'),
('userIdentity', 'string', 'userIdentity', 'string'),
('eventSource', 'string', 'eventSource', 'string'),
('tableName', 'string', 'tableName', 'string'),
('recordFormat', 'string', 'recordFormat', 'string'),
('eventID', 'string', 'eventID', 'string'),
('dynamodb.ApproximateCreationDateTime', 'long',
'ApproximateCreationDateTime', 'long'),
('dynamodb.SizeBytes', 'long', 'SizeBytes', 'long'),
('dynamodb.NewImage.id.S', 'string', 'id', 'string'),
('dynamodb.NewImage.custName.S', 'string', 'custName', 'string'),
('dynamodb.NewImage.email.S', 'string', 'email', 'string'),
('dynamodb.NewImage.registrationDate.S', 'string',
'registrationDate', 'string'),
('awsRegion', 'string', 'awsRegion', 'string')
]
new_df = ApplyMapping.apply(frame = DataSource0, mappings=your_map,
transformation_ctx = "applymapping1")
abc = new_df.toDF()
inputDf =
abc.withColumn('update_ts_dms',abc["registrationDate"]).withColumn('partitionkey',abc["id"].substr(-1,1)).withColumn('partitionkey2',abc["id"].substr(-2,1))
# glueContext.write_dynamic_frame.from_options(frame =
DynamicFrame.fromDF(inputDf, glueContext, "inputDf"), connection_type =
"marketplace.spark", connection_options = combinedConf)
glueContext.write_dynamic_frame.from_options(frame =
DynamicFrame.fromDF(inputDf, glueContext, "inputDf"), connection_type =
"custom.spark", connection_options = combinedConf)
glueContext.forEachBatch(frame = data_frame_DataSource0, batch_function =
processBatch, options = {"windowSize": "10 seconds", "checkpointLocation":
s3_path_spark})
job.commit()
```
ERROR:
```
2023-01-18T19:05:06.071+05:30Copy23/01/18 13:35:06 ERROR ProcessLauncher:
Error from Python:Traceback (most recent call last): File
"/tmp/glue_job_script.py", line 79, in <module>
glueContext.forEachBatch(frame = data_frame_DataSource0, batch_function =
processBatch, options = {"windowSize": "10 seconds", "checkpointLocation":
s3_path_spark}) File
"/opt/amazon/lib/python3.6/site-packages/awsglue/context.py", line 678, in
forEachBatch raise e File
"/opt/amazon/lib/python3.6/site-packages/awsglue/context.py", line 668, in
forEachBatch query.start().awaitTermination() File
"/opt/amazon/spark/python/lib/pyspark.zip/pyspark/sql/streaming.py", line 101,
in awaitTermination return self._jsq.awaitTermination() File
"/opt/amazon/spark/python/lib/py4j-0.10.9-src.zip/py4j/java_gateway.py", line
1305, in __call__ answer, self.gateway_client, self.target_id, self.name)
File "/opt/amazon/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 117,
in deco raise convert
ed from Nonepyspark.sql.utils.StreamingQueryException: An exception was raised
by the Python Proxy. Return Message: Traceback (most recent call last): File
"/opt/amazon/spark/python/lib/py4j-0.10.9-src.zip/py4j/java_gateway.py", line
2442, in _call_proxy return_value = getattr(self.pool[obj_id],
method)(*params) File
"/opt/amazon/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 196, in
call raise e File
"/opt/amazon/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 193, in
call self.func(DataFrame(jdf, self.sql_ctx), batch_id) File
"/opt/amazon/lib/python3.6/site-packages/awsglue/context.py", line 653, in
batch_function_with_persist batch_function(data_frame, batchId) File
"/tmp/glue_job_script.py", line 76, in processBatch
glueContext.write_dynamic_frame.from_options(frame =
DynamicFrame.fromDF(inputDf, glueContext, "inputDf"), connection_type =
"custom.spark", connection_options = combinedConf) File
"/opt/amazon/lib/python3.6/site-packages/awsgl
ue/dynamicframe.py", line 644, in from_options format_options,
transformation_ctx) File
"/opt/amazon/lib/python3.6/site-packages/awsglue/context.py", line 334, in
write_dynamic_frame_from_options format, format_options, transformation_ctx)
File "/opt/amazon/lib/python3.6/site-packages/awsglue/context.py", line 357,
in write_from_options return sink.write(frame_or_dfc) File
"/opt/amazon/lib/python3.6/site-packages/awsglue/data_sink.py", line 39, in
write return self.writeFrame(dynamic_frame_or_dfc, info) File
"/opt/amazon/lib/python3.6/site-packages/awsglue/data_sink.py", line 32, in
writeFrame return
DynamicFrame(self._jsink.pyWriteDynamicFrame(dynamic_frame._jdf, callsite(),
info), dynamic_frame.glue_ctx, dynamic_frame.name + "_errors") File
"/opt/amazon/spark/python/lib/py4j-0.10.9-src.zip/py4j/java_gateway.py", line
1305, in __call__ answer, self.gateway_client, self.target_id, self.name)
File "/opt/amazon/spark/python/lib/pyspark.zip/pyspark/sql/utils.py"
, line 111, in deco return f(*a, **kw) File
"/opt/amazon/spark/python/lib/py4j-0.10.9-src.zip/py4j/protocol.py", line 328,
in get_return_value format(target_id, ".", name),
value)py4j.protocol.Py4JJavaError: An error occurred while calling
o318.pyWriteDynamicFrame.: org.apache.hudi.exception.HoodieIOException: Deletes
issued without any prior commits at
org.apache.hudi.client.AbstractHoodieWriteClient.setWriteSchemaForDeletes(AbstractHoodieWriteClient.java:1190)
at
org.apache.hudi.client.SparkRDDWriteClient.getTableAndInitCtx(SparkRDDWriteClient.java:484)
at
org.apache.hudi.client.SparkRDDWriteClient.getTableAndInitCtx(SparkRDDWriteClient.java:448)
at
org.apache.hudi.client.SparkRDDWriteClient.delete(SparkRDDWriteClient.java:254)
at
org.apache.hudi.DataSourceUtils.doDeleteOperation(DataSourceUtils.java:229) at
org.apache.hudi.HoodieSparkSqlWriter$.write(HoodieSparkSqlWriter.scala:194) at
org.apache.hudi.DefaultSource.createRelation(DefaultSource.scala:164) at
org.apache.spark
.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:46)
at
org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:70)
at
org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:68)
at
org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:90)
at
org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:185)
at
org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:223)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at
org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:220) at
org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:181) at
org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:134)
at
org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:133)
at org.apache.spark.sql.Dat
aFrameWriter.$anonfun$runCommand$1(DataFrameWriter.scala:989) at
org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:107)
at
org.apache.spark.sql.execution.SQLExecution$.withTracker(SQLExecution.scala:232)
at
org.apache.spark.sql.execution.SQLExecution$.executeQuery$1(SQLExecution.scala:110)
at
org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$6(SQLExecution.scala:135)
at
org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:107)
at
org.apache.spark.sql.execution.SQLExecution$.withTracker(SQLExecution.scala:232)
at
org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:135)
at
org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:253)
at
org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:134)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:772) at
org.apa
che.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:68)
at
org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:989) at
org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:438)
at
org.apache.spark.sql.DataFrameWriter.saveInternal(DataFrameWriter.scala:415) at
org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:301) at
com.amazonaws.services.glue.marketplace.connector.SparkCustomDataSink.writeDynamicFrame(CustomDataSink.scala:45)
at
com.amazonaws.services.glue.DataSink.pyWriteDynamicFrame(DataSink.scala:72) at
sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498) at
py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244) at
py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.j
ava:357) at py4j.Gateway.invoke(Gateway.java:282) at
py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) at
py4j.commands.CallCommand.execute(CallCommand.java:79) at
py4j.GatewayConnection.run(GatewayConnection.java:238) at
java.lang.Thread.run(Thread.java:750)=== Streaming Query ===Identifier: [id =
9ec8a832-a17c-4dc7-b1be-8d96c8c67ba1, runId =
ab4f5b74-e3ba-4cda-92d3-c165407bcaf9]Current Committed Offsets: {}Current
Available Offsets: {KinesisSource[hudi_demo_stream_4b62e7a0]:
{"metadata":{"streamName":"hudi_demo_stream_4b62e7a0","batchId":"0"},"shardId-000000000000":{"iteratorType":"TRIM_HORIZON","iteratorPosition":""}}}Current
State: ACTIVEThread State: RUNNABLELogical Plan:Project [cast(data#18 as
string) AS $json$data_infer_schema$_temporary$#27]+- Project [UDF(data#5) AS
data#18, streamName#6, partitionKey#7, sequenceNumber#8,
approximateArrivalTimestamp#9] +- StreamingExecutionRelation
KinesisSource[hudi_demo_stream_4b62e7a0], [data#5, streamName#6, partit
ionKey#7, sequenceNumber#8, approximateArrivalTimestamp#9] | 23/01/18 13:35:06
ERROR ProcessLauncher: Error from Python:Traceback (most recent call last):
File "/tmp/glue_job_script.py", line 79, in <module>
glueContext.forEachBatch(frame = data_frame_DataSource0, batch_function =
processBatch, options = {"windowSize": "10 seconds", "checkpointLocation":
s3_path_spark}) File
"/opt/amazon/lib/python3.6/site-packages/awsglue/context.py", line 678, in
forEachBatch raise e File
"/opt/amazon/lib/python3.6/site-packages/awsglue/context.py", line 668, in
forEachBatch query.start().awaitTermination() File
"/opt/amazon/spark/python/lib/pyspark.zip/pyspark/sql/streaming.py", line 101,
in awaitTermination return self._jsq.awaitTermination() File
"/opt/amazon/spark/python/lib/py4j-0.10.9-src.zip/py4j/java_gateway.py", line
1305, in __call__ answer, self.gateway_client, self.target_id, self.name) File
"/opt/amazon/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 117, in
deco raise conver
ted from None pyspark.sql.utils.StreamingQueryException: An exception was
raised by the Python Proxy. Return Message: Traceback (most recent call last):
File "/opt/amazon/spark/python/lib/py4j-0.10.9-src.zip/py4j/java_gateway.py",
line 2442, in _call_proxy return_value = getattr(self.pool[obj_id],
method)(*params) File
"/opt/amazon/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 196, in
call raise e File
"/opt/amazon/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 193, in
call self.func(DataFrame(jdf, self.sql_ctx), batch_id) File
"/opt/amazon/lib/python3.6/site-packages/awsglue/context.py", line 653, in
batch_function_with_persist batch_function(data_frame, batchId) File
"/tmp/glue_job_script.py", line 76, in processBatch
glueContext.write_dynamic_frame.from_options(frame =
DynamicFrame.fromDF(inputDf, glueContext, "inputDf"), connection_type =
"custom.spark", connection_options = combinedConf) File
"/opt/amazon/lib/python3.6/site-packages/awsglue/dynamicframe.py"
, line 644, in from_options format_options, transformation_ctx) File
"/opt/amazon/lib/python3.6/site-packages/awsglue/context.py", line 334, in
write_dynamic_frame_from_options format, format_options, transformation_ctx)
File "/opt/amazon/lib/python3.6/site-packages/awsglue/context.py", line 357, in
write_from_options return sink.write(frame_or_dfc) File
"/opt/amazon/lib/python3.6/site-packages/awsglue/data_sink.py", line 39, in
write return self.writeFrame(dynamic_frame_or_dfc, info) File
"/opt/amazon/lib/python3.6/site-packages/awsglue/data_sink.py", line 32, in
writeFrame return
DynamicFrame(self._jsink.pyWriteDynamicFrame(dynamic_frame._jdf, callsite(),
info), dynamic_frame.glue_ctx, dynamic_frame.name + "_errors") File
"/opt/amazon/spark/python/lib/py4j-0.10.9-src.zip/py4j/java_gateway.py", line
1305, in __call__ answer, self.gateway_client, self.target_id, self.name) File
"/opt/amazon/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 111, in
deco return f(*a, **kw) File
"/opt/amazon/spark/python/lib/py4j-0.10.9-src.zip/py4j/protocol.py", line
328, in get_return_value format(target_id, ".", name), value)
py4j.protocol.Py4JJavaError: An error occurred while calling
o318.pyWriteDynamicFrame. : org.apache.hudi.exception.HoodieIOException:
Deletes issued without any prior commits at
org.apache.hudi.client.AbstractHoodieWriteClient.setWriteSchemaForDeletes(AbstractHoodieWriteClient.java:1190)
at
org.apache.hudi.client.SparkRDDWriteClient.getTableAndInitCtx(SparkRDDWriteClient.java:484)
at
org.apache.hudi.client.SparkRDDWriteClient.getTableAndInitCtx(SparkRDDWriteClient.java:448)
at
org.apache.hudi.client.SparkRDDWriteClient.delete(SparkRDDWriteClient.java:254)
at org.apache.hudi.DataSourceUtils.doDeleteOperation(DataSourceUtils.java:229)
at org.apache.hudi.HoodieSparkSqlWriter$.write(HoodieSparkSqlWriter.scala:194)
at org.apache.hudi.DefaultSource.createRelation(DefaultSource.scala:164) at
org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCom
mand.run(SaveIntoDataSourceCommand.scala:46) at
org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:70)
at
org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:68)
at
org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:90)
at
org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:185)
at
org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:223)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:220)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:181) at
org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:134)
at
org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:133)
at org.apache.spark.sql.DataFrameWriter.$anonfun$runCommand$1(DataFrameWrit
er.scala:989) at
org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:107)
at
org.apache.spark.sql.execution.SQLExecution$.withTracker(SQLExecution.scala:232)
at
org.apache.spark.sql.execution.SQLExecution$.executeQuery$1(SQLExecution.scala:110)
at
org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$6(SQLExecution.scala:135)
at
org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:107)
at
org.apache.spark.sql.execution.SQLExecution$.withTracker(SQLExecution.scala:232)
at
org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:135)
at
org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:253)
at
org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:134)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:772) at
org.apache.spark.sql.execution.SQLExecution$.withNewExe
cutionId(SQLExecution.scala:68) at
org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:989) at
org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:438)
at org.apache.spark.sql.DataFrameWriter.saveInternal(DataFrameWriter.scala:415)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:301) at
com.amazonaws.services.glue.marketplace.connector.SparkCustomDataSink.writeDynamicFrame(CustomDataSink.scala:45)
at com.amazonaws.services.glue.DataSink.pyWriteDynamicFrame(DataSink.scala:72)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498) at
py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244) at
py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357) at
py4j.Gateway.invoke(Gateway.java:282
) at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) at
py4j.commands.CallCommand.execute(CallCommand.java:79) at
py4j.GatewayConnection.run(GatewayConnection.java:238) at
java.lang.Thread.run(Thread.java:750) === Streaming Query === Identifier: [id =
9ec8a832-a17c-4dc7-b1be-8d96c8c67ba1, runId =
ab4f5b74-e3ba-4cda-92d3-c165407bcaf9] Current Committed Offsets: {} Current
Available Offsets: {KinesisSource[hudi_demo_stream_4b62e7a0]:
{"metadata":{"streamName":"hudi_demo_stream_4b62e7a0","batchId":"0"},"shardId-000000000000":{"iteratorType":"TRIM_HORIZON","iteratorPosition":""}}}
Current State: ACTIVE Thread State: RUNNABLE Logical Plan: Project
[cast(data#18 as string) AS $json$data_infer_schema$_temporary$#27] +- Project
[UDF(data#5) AS data#18, streamName#6, partitionKey#7, sequenceNumber#8,
approximateArrivalTimestamp#9] +- StreamingExecutionRelation
KinesisSource[hudi_demo_stream_4b62e7a0], [data#5, streamName#6,
partitionKey#7, sequenceNumber#8, approximateAr
rivalTimestamp#9]
-- | --
```
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