How can you achieve high availability in Apache Spark?
Answer / Shailendra Gautam
High availability in Apache Spark can be achieved through several means. One approach is to use multiple Spark applications that continuously monitor each other for failures and take over if necessary. Another method is to configure the application to run on a cluster management system like Hadoop YARN, which provides fault tolerance and automatic resource allocation.
| Is This Answer Correct ? | 0 Yes | 0 No |
Is apache spark a programming language?
What are the different levels of persistence in Spark?
What is master node in spark?
What are the advantages of DataSets?
What is DataFrames?
Describe Spark SQL?
Explain various level of persistence in Apache Spark?
What is the biggest shortcoming of Spark?
Explain the operations of Apache Spark RDD?
What do we mean by Partitions or slices?
What does rdd stand for?
Describe Accumulator in detail in Apache Spark?
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)