To use this Apache Druid feature, make sure to only load materialized-view-selection
on Broker and load materialized-view-maintenance
on Overlord. In addition, this feature currently requires a Hadoop cluster.
This feature enables Druid to greatly improve the query performance, especially when the query dataSource has a very large number of dimensions but the query only required several dimensions. This feature includes two parts. One is materialized-view-maintenance
, and the other is materialized-view-selection
.
Materialized-view-maintenance
In materialized-view-maintenance, dataSources user ingested are called “base-dataSource”. For each base-dataSource, we can submit derivativeDataSource
supervisors to create and maintain other dataSources which we called “derived-dataSource”. The dimensions and metrics of derived-dataSources are the subset of base-dataSource’s. The derivativeDataSource
supervisor is used to keep the timeline of derived-dataSource consistent with base-dataSource. Each derivativeDataSource
supervisor is responsible for one derived-dataSource.
A sample derivativeDataSource supervisor spec is shown below:
{
"type": "derivativeDataSource",
"baseDataSource": "wikiticker",
"dimensionsSpec": {
"dimensions": [
"isUnpatrolled",
"metroCode",
"namespace",
"page",
"regionIsoCode",
"regionName",
"user"
]
},
"metricsSpec": [
{
"name": "count",
"type": "count"
},
{
"name": "added",
"type": "longSum",
"fieldName": "added"
}
],
"tuningConfig": {
"type": "hadoop"
}
}
Supervisor Configuration
Field | Description | Required |
---|---|---|
Type | The supervisor type. This should always be derivativeDataSource . | yes |
baseDataSource | The name of base dataSource. This dataSource data should be already stored inside Druid, and the dataSource will be used as input data. | yes |
dimensionsSpec | Specifies the dimensions of the data. These dimensions must be the subset of baseDataSource’s dimensions. | yes |
metricsSpec | A list of aggregators. These metrics must be the subset of baseDataSource’s metrics. See aggregations. | yes |
tuningConfig | TuningConfig must be HadoopTuningConfig. See Hadoop tuning config. | yes |
dataSource | The name of this derived dataSource. | no(default=baseDataSource-hashCode of supervisor) |
hadoopDependencyCoordinates | A JSON array of Hadoop dependency coordinates that Druid will use, this property will override the default Hadoop coordinates. Once specified, Druid will look for those Hadoop dependencies from the location specified by druid.extensions.hadoopDependenciesDir | no |
classpathPrefix | Classpath that will be prepended for the Peon process. | no |
context | See below. | no |
Context
Field | Description | Required |
---|---|---|
maxTaskCount | The max number of tasks the supervisor can submit simultaneously. | no(default=1) |
Materialized-view-selection
In materialized-view-selection, we implement a new query type view
. When we request a view query, Druid will try its best to optimize the query based on query dataSource and intervals.
A sample view query spec is shown below:
{
"queryType": "view",
"query": {
"queryType": "groupBy",
"dataSource": "wikiticker",
"granularity": "all",
"dimensions": [
"user"
],
"limitSpec": {
"type": "default",
"limit": 1,
"columns": [
{
"dimension": "added",
"direction": "descending",
"dimensionOrder": "numeric"
}
]
},
"aggregations": [
{
"type": "longSum",
"name": "added",
"fieldName": "added"
}
],
"intervals": [
"2015-09-12/2015-09-13"
]
}
}
There are 2 parts in a view query:
Field | Description | Required |
---|---|---|
queryType | The query type. This should always be view | yes |
query | The real query of this view query. The real query must be groupBy, topN, or timeseries type. | yes |
Note that Materialized View is currently designated as experimental. Please make sure the time of all processes are the same and increase monotonically. Otherwise, some unexpected errors may happen on query results.