19.4. Repartitioned and Replicated Joins


Presto can perform two types of distributed joins: repartitioned and replicated. In a repartitioned join, both inputs to a join get hash partitioned across the nodes of the cluster. In a replicated join, one of the inputs is distributed to all of the nodes on the cluster that have data from the other input.

Repartitioned joins are good for larger inputs, as they need less memory on each node and allow Presto to handle larger joins overall. However, they can be much slower than replicated joins because they can require more data to be transferred over the network for tables that differ greatly in size.

Replicated joins can be much faster than repartitioned joins if the replicated table is small enough to fit in memory and much smaller than the other input. But, if the replicated input is too large, the query can run out of memory.

Choosing the Distribution Type in Presto

The choice between replicated and repartitioned joins is controlled by the property join-distribution-type. Its possible values are repartitioned, replicated, and automatic. The default value is repartitioned. The property can also be set per session using the session property join_distribution_type.

SET SESSION join_distribution_type = 'automatic';

When join-distribution-type is set to repartitioned, repartitioned distribution is used. When it is set to replicated, replicated distribution is used. In replicated mode, the right input to the join is the one that gets replicated.

When the property is set to automatic, the optimizer will choose which type of join to use based on the size of the join inputs. The smaller table from a join will be replicated if the following two conditions hold:

  1. It is smaller than coefficient * query.max-memory-per-node The coefficient defaults to 0.01. It can be set using the property small-table-coefficient or per session using the session property small_table_coefficient.

    SET SESSION small_table_coefficient = 0.05;

    The coefficient is there to ensure that queries do not exceed query.max-memory-per-node, even when they contain multiple joins. The property should be set to prevent out of memory errors for the most complex queries while within that framework allowing replicated joins when optimal and possible.

  2. It is n times smaller than the other table in a join, where n is the number of nodes in the cluster.

If neither input meets these conditions, a repartitioned join is performed.