What is the meaning of speculative execution in Hadoop? Why is it important?
- 1 Answers
- 1123 Views
- I also Faced
- E-Mail Answers
Answer / Priyanka Chauhan
Speculative Execution in Hadoop refers to the process of executing multiple tasks for a single job in parallel, with the expectation that some of them may fail. The failed tasks are then re-executed using results from successful tasks or new input data as needed. Speculative execution helps reduce task completion time and improve overall system performance.
| Is This Answer Correct ? | 0 Yes | 0 No |
What is the difference between Hadoop and Traditional RDBMS?
What is version-id mismatch error in hadoop?
What is a 'block' in HDFS?
What is the difference between traditional RDBMS and Hadoop?
Why we cannot do aggregation (addition) in a mapper? Why we require reducer for that?
What Mapper does?
What is the difference between hadoop and other data processing tools?
How blocks are distributed among all data nodes for a particular chunk of data?
How many instances of tasktracker run on a hadoop cluster?
Whats is distributed cache in hadoop?
Why is Apache Spark faster than Apache Hadoop?
What is DistributedCache and its purpose?
-
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)
