What happens if rdd partition is lost due to worker node failure?
Answer / Anurag Chaturvedi
When an RDD partition is lost due to a worker node failure, Spark will recompute the missing data by resending the tasks that were executing on the failed worker node to another available worker. This process may cause a delay in task completion but ensures data integrity and availability.
| Is This Answer Correct ? | 0 Yes | 0 No |
What is shark?
What is difference between dataset and dataframe in spark?
Explain what are the various types of Transformation on DStream?
Different Running Modes of Apache Spark
What are the ways in which Apache Spark handles accumulated Metadata?
Explain the filter transformation?
How do I install spark?
Why do we need rdd in spark?
What are the features of spark rdd?
Explain sum(), max(), min() operation in Apache Spark?
What is an "Accumulator"?
How is streaming implemented in spark? Explain with examples.
Apache Hadoop (394)
MapReduce (354)
Apache Hive (345)
Apache Pig (225)
Apache Spark (991)
Apache HBase (164)
Apache Flume (95)
Apache Impala (72)
Apache Cassandra (392)
Apache Mahout (35)
Apache Sqoop (82)
Apache ZooKeeper (65)
Apache Ambari (93)
Apache HCatalog (34)
Apache HDFS Hadoop Distributed File System (214)
Apache Kafka (189)
Apache Avro (26)
Apache Presto (15)
Apache Tajo (26)
Hadoop General (407)