Writer scaling properties#
By default, the number of writer tasks is static. Enabling writer scaling allows Trino to dynamically scale out the number of writer tasks rather than allocating a fixed number of tasks. Additional tasks are added when the average amount of physical data per writer is above a minimum threshold, but only if the query is bottlenecked on writing.
Writer scaling is useful with connectors like Hive that produce one or more files per writer – reducing the number of writers results in a larger average file size. However, writer scaling can have a small impact on query wall time due to the decreased writer parallelism while the writer count ramps up to match the needs of the query.
Enable writer scaling. This can be specified on a per-query basis
scale_writers session property.
The minimum amount of data that must be written by a writer task before
another writer is eligible to be added. Each writer task may have multiple
writers, controlled by
task.writer-count, thus this value is effectively
divided by the number of writers per task. This can be specified on a
per-query basis using the
writer_min_size session property.
Enable preferred write partitioning. When set to
true and more than the
minimum number of partitions, set in
are written, each partition is written by a separate writer. As a result, for some connectors such as the
Hive connector, only a single new file is written per partition, instead of
multiple files. Partition writer assignments are distributed across worker
nodes for parallel processing.
The minimum number of written partitions that is required to use connector
preferred write partitioning. If the number of partitions cannot be
estimated from the statistics, then preferred write partitioning is not used.
If the threshold value is
preferred write partitioning is always