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Editorial Team
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Asked: 2026-05-24T08:03:52+00:00

When you join tables which are distributed on the same key and used these

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When you join tables which are distributed on the same key and used these key columns in the join condition, then each SPU (machine) in netezza works 100% independent of the other (see nz-interview).

In hive, there’s bucketed map join, but the distribution of the files representing the tables to datanode is the responsibility of HDFS, it’s not done according to hive CLUSTERED BY key!

so suppose I have 2 tables, CLUSTERED BY the same key, and I join by that key – can hive get a guarantee from HDFS that matching buckets will sit on the same node? or will it always have to move the matching bucket of the small table to the datanode containing the big table bucket?

Thanks, ido

(note: this is a better phrasing of my previous question: How does hive/hadoop assures that each mapper works on data that is local for it?)

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1 Answer

  1. Editorial Team

    I think it is not possible to tell to HDFS where to store blocks of data.
    I can consider the following trick, which will do for small clusters – to increase replication factor for one of the tables to the number close or equal to the number of nodes in the cluster.
    As a result – during join process appropriate data will be almost always (or always) present on the required node.

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