![]() ![]() Job attempt directory in $dest/_temporary/$jobAttemptId/ contains all output of the job in progress every task attempt is allocated its own task attempt dir $dest/_temporary/$jobAttemptId/_temporary/$taskAttemptIdĪll work for a task is written under the task attempt directory. File Output Committer V1 and V2 File Output Committer V1 and V2 Commit algorithms Task attempt execution (V1 and V2) It is possible for multiple task attempts to get their data into the output directory tree, and if a job fails/is aborted before the job is committed, thie output is visible. The v2 algorithm is not considered safe because the output is visible when individual tasks commit, rather than being delayed until job commit. The v1 algorithm is resilient to all forms of task failure, but slow when committing the final aggregate output as it renames each newly created file to the correct place in the table one by one. The committer built into hadoop-mapreduce-client-core module is the FileOutputCommitter. Continuity of correctness: once a job is committed, the output of any failed, aborted, or unsuccessful task MUST NO appear at some point in the future.įor Hive’s classic hierarchical-directory-structured tables, job committing requires the output of all committed tasks to be put into the correct location in the directory tree.Abortable: jobs and tasks may be aborted prior to job commit, after which their output is not visible.Concurrent: When multiple tasks are committed in parallel the output is the same as when the task commits are serialized.Exclusive: the output of unsuccessful tasks is not present.Complete: the output includes the work of all successful tasks.The purpose of a committer is to ensure that the complete output of a job ends up in the destination, even in the presence of failures of tasks. Taking the output of a Task Attempt and making it the final/exclusive result of that “successful” Task.Īggregating all the outputs of all committed tasks and producing the final results of the job. This is always underneath the destination directory, so as to ensure it is in the same encryption zone as HDFS, storage volume in other filesystems, etc.ĭirectory under the Job Attempt Directory where task attempts create subdiretories for their own workĭirectory exclusive for each task attempt under which files are written The Task ID + an attempt counter.Ī temporary directory used by the job attempt. It may fail, in which case MR/spark will schedule another.Ī unique ID for the task attempt. Usually starts at 0 and is used in filenames (part-0000, part-001, etc.)Īn attempt to perform a task. Spark says “start again from scratch”Ī subsection of a job, such as processing one file, or one part of a file ![]() MR supports multiple Job attempts with recovery on partial job failure. ![]() In spark, this is a single stage in a chain of workĪ single attempt at a job. The spark process scheduling the work and choreographing the commit operation.
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