Table of Contents

Metadata Storage

The Metadata Storage is an external dependency of Druid. Druid uses it to store various metadata about the system, but not to store the actual data. There are a number of tables used for various purposes described below.

Derby is the default metadata store for Druid, however, it is not suitable for production. MySQL and PostgreSQL are more production suitable metadata stores.

Derby is not suitable for production use as a metadata store. Use MySQL or PostgreSQL instead.

Using derby

Add the following to your Druid configuration.

druid.metadata.storage.type=derby
druid.metadata.storage.connector.connectURI=jdbc:derby://localhost:1527//opt/var/druid_state/derby;create=true

MySQL

See mysql-metadata-storage extension documentation.

PostgreSQL

See postgresql-metadata-storage.

Metadata Storage Tables

Segments Table

This is dictated by the druid.metadata.storage.tables.segments property.

This table stores metadata about the segments that are available in the system. The table is polled by the Coordinator to determine the set of segments that should be available for querying in the system. The table has two main functional columns, the other columns are for indexing purposes.

The used column is a boolean "tombstone". A 1 means that the segment should be "used" by the cluster (i.e. it should be loaded and available for requests). A 0 means that the segment should not be actively loaded into the cluster. We do this as a means of removing segments from the cluster without actually removing their metadata (which allows for simpler rolling back if that is ever an issue).

The payload column stores a JSON blob that has all of the metadata for the segment (some of the data stored in this payload is redundant with some of the columns in the table, that is intentional). This looks something like

{
 "dataSource":"wikipedia",
 "interval":"2012-05-23T00:00:00.000Z/2012-05-24T00:00:00.000Z",
 "version":"2012-05-24T00:10:00.046Z",
 "loadSpec":{
    "type":"s3_zip",
    "bucket":"bucket_for_segment",
    "key":"path/to/segment/on/s3"
 },
 "dimensions":"comma-delimited-list-of-dimension-names",
 "metrics":"comma-delimited-list-of-metric-names",
 "shardSpec":{"type":"none"},
 "binaryVersion":9,
 "size":size_of_segment,
 "identifier":"wikipedia_2012-05-23T00:00:00.000Z_2012-05-24T00:00:00.000Z_2012-05-23T00:10:00.046Z"
}

Note that the format of this blob can and will change from time-to-time.

Rule Table

The rule table is used to store the various rules about where segments should land. These rules are used by the Coordinator when making segment (re-)allocation decisions about the cluster.

Config Table

The config table is used to store runtime configuration objects. We do not have many of these yet and we are not sure if we will keep this mechanism going forward, but it is the beginnings of a method of changing some configuration parameters across the cluster at runtime.

There are also a number of tables created and used by the Indexing Service in the course of its work.

Audit Table

The Audit table is used to store the audit history for configuration changes e.g rule changes done by Coordinator and other config changes.

Accessed By:

The Metadata Storage is accessed only by:

  1. Indexing Service Nodes (if any)
  2. Realtime Nodes (if any)
  3. Coordinator Nodes

Thus you need to give permissions (eg in AWS Security Groups) only for these machines to access the Metadata storage.