Lookups

Lookups are a concept in Apache Druid where dimension values are (optionally) replaced with new values, allowing join-like functionality. Applying lookups in Druid is similar to joining a dimension table in a data warehouse. See dimension specs for more information. For the purpose of these documents, a "key" refers to a dimension value to match, and a "value" refers to its replacement. So if you wanted to map appid-12345 to Super Mega Awesome App then the key would be appid-12345 and the value would be Super Mega Awesome App.

It is worth noting that lookups support not just use cases where keys map one-to-one to unique values, such as country code and country name, but also support use cases where multiple IDs map to the same value, e.g. multiple app-ids mapping to a single account manager. When lookups are one-to-one, Druid is able to apply additional optimizations at query time; see Query execution below for more details.

Lookups do not have history. They always use the current data. This means that if the chief account manager for a particular app-id changes, and you issue a query with a lookup to store the app-id to account manager relationship, it will return the current account manager for that app-id REGARDLESS of the time range over which you query.

If you require data time range sensitive lookups, such a use case is not currently supported dynamically at query time, and such data belongs in the raw denormalized data for use in Druid.

Lookups are generally preloaded in-memory on all servers. But very small lookups (on the order of a few dozen to a few hundred entries) can also be passed inline in native queries time using the "map" lookup type. Refer to the dimension specs documentation for details.

Other lookup types are available as extensions, including:

Globally cached lookups from local files, remote URIs, or JDBC through lookups-cached-global.
Globally cached lookups from a Kafka topic through kafka-extraction-namespace.

Query Syntax

In Druid SQL, lookups can be queried using the LOOKUP function, for example:

SELECT
  LOOKUP(store, 'store_to_country') AS country,
  SUM(revenue)
FROM sales
GROUP BY 1

They can also be queried using the JOIN operator:

SELECT
  store_to_country.v AS country,
  SUM(sales.revenue) AS country_revenue
FROM
  sales
  INNER JOIN lookup.store_to_country ON sales.store = store_to_country.k
GROUP BY 1

In native queries, lookups can be queried with dimension specs or extraction functions.

Query Execution

When executing an aggregation query involving lookup functions, like the SQL LOOKUP function, Druid can decide to apply them while scanning and aggregating rows, or to apply them after aggregation is complete. It is more efficient to apply lookups after aggregation is complete, so Druid will do this if it can. Druid decides this by checking if the lookup is marked as "injective" or not. In general, you should set this property for any lookup that is naturally one-to-one, to allow Druid to run your queries as fast as possible.

Injective lookups should include all possible keys that may show up in your dataset, and should also map all keys to unique values. This matters because non-injective lookups may map different keys to the same value, which must be accounted for during aggregation, lest query results contain two result values that should have been aggregated into one.

This lookup is injective (assuming it contains all possible keys from your data):

1 -> Foo
2 -> Bar
3 -> Billy

But this one is not, since both "2" and "3" map to the same value:

1 -> Foo
2 -> Bar
3 -> Bar

To tell Druid that your lookup is injective, you must specify "injective" : true in the lookup configuration. Druid will not detect this automatically.

Currently, the injective lookup optimization is not triggered when lookups are inputs to a join datasource. It is only used when lookup functions are used directly, without the join operator.

Dynamic Configuration

The following documents the behavior of the cluster-wide config which is accessible through the Coordinator. The configuration is propagated through the concept of "tier" of servers. A "tier" is defined as a group of services which should receive a set of lookups. For example, you might have all Historicals be part of __default, and Peons be part of individual tiers for the datasources they are tasked with. The tiers for lookups are completely independent of Historical tiers.

These configs are accessed using JSON through the following URI template

http://<COORDINATOR_IP>:<PORT>/druid/coordinator/v1/lookups/config/{tier}/{id}

All URIs below are assumed to have http://<COORDINATOR_IP>:<PORT> prepended.

If you have NEVER configured lookups before, you MUST post an empty json object {} to /druid/coordinator/v1/lookups/config to initialize the configuration.

These endpoints will return one of the following results:

404 if the resource is not found
400 if there is a problem in the formatting of the request
202 if the request was accepted asynchronously (POST and DELETE)
200 if the request succeeded (GET only)

Configuration propagation behavior

The configuration is propagated to the query serving processes (Broker / Router / Peon / Historical) by the Coordinator. The query serving processes have an internal API for managing lookups on the process and those are used by the Coordinator. The Coordinator periodically checks if any of the processes need to load/drop lookups and updates them appropriately.

Please note that only 2 simultaneous lookup configuration propagation requests can be concurrently handled by a single query serving process. This limit is applied to prevent lookup handling from consuming too many server HTTP connections.

API

See Lookups API for reference on configuring lookups and lookup status.

Configuration

See Lookups Dynamic Configuration for Coordinator configuration.

To configure a Broker / Router / Historical / Peon to announce itself as part of a lookup tier, use following properties.

Property	Description	Default
`druid.lookup.lookupTier`	The tier for lookups for this process. This is independent of other tiers.	`__default`
`druid.lookup.lookupTierIsDatasource`	For some things like indexing service tasks, the datasource is passed in the runtime properties of a task. This option fetches the tierName from the same value as the datasource for the task. It is suggested to only use this as Peon options for the indexing service, if at all. If true, `druid.lookup.lookupTier` MUST NOT be specified	`"false"`

To configure the behavior of the dynamic configuration manager, use the following properties on the Coordinator:

Property	Description	Default
`druid.manager.lookups.hostTimeout`	Timeout (in ms) PER HOST for processing request	`2000`(2 seconds)
`druid.manager.lookups.allHostTimeout`	Timeout (in ms) to finish lookup management on all the processes.	`900000`(15 mins)
`druid.manager.lookups.period`	How long to pause between management cycles	`120000`(2 mins)
`druid.manager.lookups.threadPoolSize`	Number of service processes that can be managed concurrently	`10`

Saving configuration across restarts

It is possible to save the configuration across restarts such that a process will not have to wait for Coordinator action to re-populate its lookups. To do this the following property is set:

Property	Description	Default
`druid.lookup.snapshotWorkingDir`	Working path used to store snapshot of current lookup configuration, leaving this property null will disable snapshot/bootstrap utility	null
`druid.lookup.enableLookupSyncOnStartup`	Enable the lookup synchronization process with Coordinator on startup. The queryable processes will fetch and load the lookups from the Coordinator instead of waiting for the Coordinator to load the lookups for them. Users may opt to disable this option if there are no lookups configured in the cluster.	true
`druid.lookup.numLookupLoadingThreads`	Number of threads for loading the lookups in parallel on startup. This thread pool is destroyed once startup is done. It is not kept during the lifetime of the JVM	Available Processors / 2
`druid.lookup.coordinatorFetchRetries`	How many times to retry to fetch the lookup bean list from Coordinator, during the sync on startup.	3
`druid.lookup.lookupStartRetries`	How many times to retry to start each lookup, either during the sync on startup, or during the runtime.	3
`druid.lookup.coordinatorRetryDelay`	How long to delay (in millis) between retries to fetch lookup list from the Coordinator during the sync on startup.	60_000

Introspect a Lookup

The Broker provides an API for lookup introspection if the lookup type implements a LookupIntrospectHandler.

A GET request to /druid/v1/lookups/introspect/{lookupId} will return the map of complete values.

ex: GET /druid/v1/lookups/introspect/nato-phonetic

{
    "A": "Alfa",
    "B": "Bravo",
    "C": "Charlie",
    ...
    "Y": "Yankee",
    "Z": "Zulu",
    "-": "Dash"
}

The list of keys can be retrieved via GET to /druid/v1/lookups/introspect/{lookupId}/keys"

ex: GET /druid/v1/lookups/introspect/nato-phonetic/keys

[
    "A",
    "B",
    "C",
    ...
    "Y",
    "Z",
    "-"
]

A GET request to /druid/v1/lookups/introspect/{lookupId}/values" will return the list of values.

ex: GET /druid/v1/lookups/introspect/nato-phonetic/values

[
    "Alfa",
    "Bravo",
    "Charlie",
    ...
    "Yankee",
    "Zulu",
    "Dash"
]

Ingestion concepts

SQL-based batch

Streaming

Classic batch

Druid SQL

Concepts

Native query types

Native query components

HTTP APIs

Java APIs

Security

Performance tuning

Monitoring

Misc