SQL-based ingestion is not available in Polaris yet.
Apache Druid supports SQL-based ingestion using the bundled
druid-multi-stage-query extension. The extension is enabled by default.
This extension adds a multi-stage query task engine for SQL that allows running SQL
INSERT and REPLACE statements as batch tasks. As an experimental feature,
the task engine also supports running
SELECT queries as batch tasks.
SELECT capabilities are available in the multi-stage query (MSQ) task engine, with certain exceptions listed on the Known
issues page. This allows great flexibility to apply transformations, filters, JOINs,
aggregations, and so on as part of
INSERT ... SELECT and
REPLACE ... SELECT statements. This also allows in-database
transformation: creating new tables based on queries of other tables.
Controller: An indexing service task of type
query_controllerthat manages the execution of a query. There is one controller task per query.
Worker: Indexing service tasks of type
query_workerthat execute a query. There can be multiple worker tasks per query. Internally, the tasks process items in parallel using their processing pools (up to
druid.processing.numThreadsof execution parallelism within a worker task).
Stage: A stage of query execution that is parallelized across worker tasks. Workers exchange data with each other between stages.
Partition: A slice of data output by worker tasks. In INSERT or REPLACE queries, the partitions of the final stage become Druid segments.
Shuffle: Workers exchange data between themselves on a per-partition basis in a process called shuffling. During a shuffle, each output partition is sorted by a clustering key.
- Read about key concepts to learn more about how SQL-based ingestion and multi-stage queries work.
- Check out the examples to see SQL-based ingestion in action.
- Explore the Query view to get started in the web console.