Some of the information has been given in the earlier checkpoint section. However, to make the link more explicitly clear, I have updated it to this. 

A system that is required to operate 24/7 needs to be able tolerate the failure of the driver node as well. Spark Streaming does this by saving the state of the DStream computation periodically to     a HDFS file, that can be used to restart the streaming computation in the event of a failure of the driver node. This checkpointing is enabled by setting a HDFS directory for checkpointing using `ssc.checkpoint(<checkpoint directory>)` as described [earlier](#rdd-checkpointing-within-dstreams) .