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Metadata Storage
The Metadata Storage is an external dependency of Apache Druid (incubating). 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.
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.
Adding custom dbcp properties
NOTE: These properties are not settable through the druid.metadata.storage.connector.dbcp properties : username, password, connectURI, validationQuery, testOnBorrow. These must be set through druid.metadata.storage.connector properties.
Example supported properties:
druid.metadata.storage.connector.dbcp.maxConnLifetimeMillis=1200000
druid.metadata.storage.connector.dbcp.defaultQueryTimeout=30000
See BasicDataSource Configuration for full list.
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.
Task-related Tables
There are also a number of tables created and used by the Overlord and MiddleManager when managing tasks.
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:
- Indexing Service Processes (if any)
- Realtime Processes (if any)
- Coordinator Processes
Thus you need to give permissions (eg in AWS Security Groups) only for these machines to access the Metadata storage.