Apache Ignite Spark Integration persists data to Ignite error - apache-spark

Question

I want to persist the DataFrame data to the ignite table, and native debugging is normal. When running on spark on yarn, it always reports an error.
df.write
.format(IgniteDataFrameSettings.FORMAT_IGNITE)
.option(IgniteDataFrameSettings.OPTION_CONFIG_FILE, "META-INF/default-config.xml")
.option(IgniteDataFrameSettings.OPTION_STREAMER_ALLOW_OVERWRITE, true)
.option(IgniteDataFrameSettings.OPTION_CREATE_TABLE_PRIMARY_KEY_FIELDS, "primary_key")
.option(IgniteDataFrameSettings.OPTION_STREAMER_FLUSH_FREQUENCY, 10000)
.option(IgniteDataFrameSettings.OPTION_TABLE, "tb_name")
.option(IgniteDataFrameSettings.OPTION_CREATE_TABLE_PARAMETERS, "template=partitioned,backups=0,affinityKey=groupcode")
.mode(SaveMode.Overwrite)
.save()
This is spark config
/data/spark-2.3.0-bin-hadoop2.7/bin/spark-submit\
--queue default\
--class cn.com.DataProcess\
--name DataProcess\
--master yarn\
--deploy-mode client \
--conf spark.default.parallelism=20\
--conf spark.executor.extraClassPath=/data/ignite/*\
--conf spark.driver.extraClassPath=/data/ignite/*\
--conf spark.driver.extraJavaOptions=-Dfile.encoding=utf8\
--conf spark.executor.extraJavaOptions=-Dfile.encoding=utf8\
--num-executors 6\
--executor-memory 1G\
--total-executor-cores 6\
--jars /data/ignite/service-2.0-SNAPSHOT-jar-with-dependencies.jar /data/ignite/service-2.0-SNAPSHOT.jar
Error stack:
Job aborted due to stage failure: Task 6 in stage 3.0 failed 4 times, most recent failure: Lost task 6.3 in stage 3.0 (TID 451, hadoop-slave2, executor 4): java.util.NoSuchElementException: None.get
at scala.None$.get(Option.scala:347)
at scala.None$.get(Option.scala:345)
at org.apache.ignite.spark.impl.QueryHelper$.org$apache$ignite$spark$impl$QueryHelper$$savePartition(QueryHelper.scala:155)
at org.apache.ignite.spark.impl.QueryHelper$$anonfun$saveTable$1.apply(QueryHelper.scala:117)
at org.apache.ignite.spark.impl.QueryHelper$$anonfun$saveTable$1.apply(QueryHelper.scala:116)
at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$29.apply(RDD.scala:929)
at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$29.apply(RDD.scala:929)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2067)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2067)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Which friend has encountered this problem, please help me！
I found the source code based on the error message and judged that it should be the error suggested here。
private def savePartition(iterator: Iterator[Row],
insertQry: String,
tblName: String,
ctx: IgniteContext,
streamerAllowOverwrite: Option[Boolean],
streamerFlushFrequency: Option[Long],
streamerPerNodeBufferSize: Option[Int],
streamerPerNodeParallelOperations: Option[Int]
): Unit = {
**val tblInfo = sqlTableInfo[Any, Any](ctx.ignite(), tblName).get**
val streamer = ctx.ignite().dataStreamer(tblInfo._1.getName)
}
But I don't understand why this happens. Both cache name and table name exist. Is my code used incorrectly?