Beginning offset 115204574 is after the ending offset 115204516 for topic

We are getting this issue in production and Sparks consumer dying because of Off Set issue.

We observed the following error in Kafka Broker

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[2019-03-18 14:40:14,100] WARN Unable to reconnect to ZooKeeper service, session 0x1692e9ff4410004 has expired (org.apache.zookeeper.ClientCnxn)
[2019-03-18 14:40:14,100] INFO Unable to reconnect to ZooKeeper service, session 0x1692e9ff4410004 has expired, closing socket connection (org.apache.zook
eeper.ClientCnxn)

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Sparks Job died with the following error:

ERROR 2019-03-18 07:40:57,178 7924 org.apache.spark.executor.Executor [Executor task launch worker for task 16] Exception in task 27.0 in stage 0.0 (TID 16)
java.lang.AssertionError: assertion failed: Beginning offset 115204574 is after the ending offset 115204516 for topic <topic_name> partition 37. You either provided an invalid fromOffset, or the Kafka topic has been damaged
at scala.Predef$.assert(Predef.scala:170)
at org.apache.spark.streaming.kafka010.KafkaRDD.compute(KafkaRDD.scala:175)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$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)