Abhinav Choudhury created SPARK-29639:
-----------------------------------------
Summary: Spark Kafka connector 0.10.0 generates incorrect end offsets for micro
batch
Key: SPARK-29639
URL: https://issues.apache.org/jira/browse/SPARK-29639
Project: Spark
Issue Type: Bug
Components: Input/Output, Structured Streaming
Affects Versions: 2.4.0
Reporter: Abhinav Choudhury
We have been running a Spark structured job on production for more than a week now. Put simply,
it reads data from source Kafka topics (with 4 partitions) and writes to another kafka topic.
Everything has been running fine until the job started failing with the following error:
{noformat}
Driver stacktrace:
=== Streaming Query ===
Identifier: MetricComputer [id = af26bab1-0d89-4766-934e-ad5752d6bb08, runId = 613a21ad-86e3-4781-891b-17d92c18954a]
Current Committed Offsets: {KafkaV2[Subscribe[kafka-topic-name]]: {"kafka-topic-name":
{"2":10458347,"1":10460151,"3":10475678,"0":9809564}
}}
Current Available Offsets: {KafkaV2[Subscribe[kf-adsk-inquirystep]]: {"kf-adsk-inquirystep":
{"2":10458347,"1":10460151,"3":10475678,"0":10509527}
}}
Current State: ACTIVE
Thread State: RUNNABLE
<-- Removed Logical plan -->
Some data may have been lost because they are not available in Kafka any more; either the
data was aged out by Kafka or the topic may have been deleted before all the data in the
topic was processed. If you don't want your streaming query to fail on such cases, set the
source option "failOnDataLoss" to "false".{noformat}
Configuration:
{noformat}
Spark 2.4.0
Spark-sql-kafka 0.10{noformat}
Looking at the Spark structured streaming query progress logs, it seems like the endOffsets
computed for the next batch was actually smaller than the starting offset:
*Microbatch Trigger 1:*
{noformat}
2019/10/26 23:53:51 INFO utils.Logging[26]: 2019-10-26 23:53:51.767 : ( : Query {
"id" : "99fe6c51-9f4a-4f6f-92d3-3c336ef5e06b",
"runId" : "2d20d633-2768-446c-845b-893243361422",
"name" : "StreamingProcessorName",
"timestamp" : "2019-10-26T23:53:51.741Z",
"batchId" : 2145898,
"numInputRows" : 0,
"inputRowsPerSecond" : 0.0,
"processedRowsPerSecond" : 0.0,
"durationMs" : {
"getEndOffset" : 0,
"setOffsetRange" : 9,
"triggerExecution" : 9
},
"stateOperators" : [ ],
"sources" : [ {
"description" : "KafkaV2[Subscribe[kafka-topic-name]]",
"startOffset" : {
"kafka-topic-name" : {
"2" : 10452513,
"1" : 10454326,
"3" : 10469196,
"0" : 10503762
}
},
"endOffset" : {
"kafka-topic-name" : {
"2" : 10452513,
"1" : 10454326,
"3" : 10469196,
"0" : 10503762
}
},
"numInputRows" : 0,
"inputRowsPerSecond" : 0.0,
"processedRowsPerSecond" : 0.0
} ],
"sink" : {
"description" : "ForeachBatchSink"
}
} in progress{noformat}
*Next micro batch trigger:*
{noformat}
2019/10/26 23:53:53 INFO utils.Logging[26]: 2019-10-26 23:53:53.951 : ( : Query {
"id" : "99fe6c51-9f4a-4f6f-92d3-3c336ef5e06b",
"runId" : "2d20d633-2768-446c-845b-893243361422",
"name" : "StreamingProcessorName",
"timestamp" : "2019-10-26T23:53:52.907Z",
"batchId" : 2145898,
"numInputRows" : 0,
"inputRowsPerSecond" : 0.0,
"processedRowsPerSecond" : 0.0,
"durationMs" : {
"addBatch" : 350,
"getBatch" : 4,
"getEndOffset" : 0,
"queryPlanning" : 102,
"setOffsetRange" : 24,
"triggerExecution" : 1043,
"walCommit" : 349
},
"stateOperators" : [ ],
"sources" : [ {
"description" : "KafkaV2[Subscribe[kafka-topic-name]]",
"startOffset" : {
"kafka-topic-name" : {
"2" : 10452513,
"1" : 10454326,
"3" : 10469196,
"0" : 10503762
}
},
"endOffset" : {
"kafka-topic-name" : {
"2" : 10452513,
"1" : 10454326,
"3" : 9773098,
"0" : 10503762
}
},
"numInputRows" : 0,
"inputRowsPerSecond" : 0.0,
"processedRowsPerSecond" : 0.0
} ],
"sink" : {
"description" : "ForeachBatchSink"
}
} in progress{noformat}
Notice that for partition 3 of the kafka topic, the endOffsets are actually smaller than the
starting offsets!
Checked the HDFS checkpoint dir and the checkpointed offsets look fine and point to the last
committed offsets
Why is the end offset for a partition being computed to a smaller value?
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