Developing on Apache Druid
Druid's codebase consists of several major components. For developers interested in learning the code, this document provides a high level overview of the main components that make up Druid and the relevant classes to start from to learn the code.
Data in Druid is stored in a custom column format known as a segment. Segments are composed of
different types of columns.
Column.java and the classes that extend it is a great place to looking into the storage format.
Raw data is ingested in
IncrementalIndex.java, and segments are created in
Druid segments are memory mapped in
IndexIO.java to be exposed for querying.
Most of the logic related to Druid queries can be found in the Query* classes. Druid leverages query runners to run queries.
Query runners often embed other query runners and each query runner adds on a layer of logic. A good starting point to trace
the query logic is to start from
Most of the coordination logic for Historical processes is on the Druid Coordinator. The starting point here is
Most of the coordination logic for (real-time) ingestion is in the Druid indexing service. The starting point here is
Druid loads data through
FirehoseFactory.java classes. Firehoses often wrap other firehoses, where, similar to the design of the
query runners, each firehose adds a layer of logic, and the persist and hand-off logic is in
Hadoop-based Batch Ingestion
The two main Hadoop indexing classes are
HadoopDruidDetermineConfigurationJob.java for the job to determine how many Druid
segments to create, and
HadoopDruidIndexerJob.java, which creates Druid segments.
At some point in the future, we may move the Hadoop ingestion code out of core Druid.
Druid currently has two internal UIs. One is for the Coordinator and one is for the Overlord.
At some point in the future, we will likely move the internal UI code out of core Druid.
We welcome contributions for new client libraries to interact with Druid. See the Community and third-party libraries page for links to existing client libraries.