Package org.apache.druid.query

Class InlineDataSource

java.lang.Object
org.apache.druid.query.LeafDataSource
org.apache.druid.query.InlineDataSource
All Implemented Interfaces:
Cacheable, DataSource
public class InlineDataSource extends LeafDataSource
Represents an inline datasource, where the rows are embedded within the DataSource object itself.

The rows are backed by an Iterable, which can be lazy or not. Lazy datasources will only be iterated if someone calls getRows() and iterates the result, or until someone calls getRowsAsList().

  • Method Details

    • fromIterable

      public static InlineDataSource fromIterable(Iterable<Object[]> rows, RowSignature signature)
      Creates an inline datasource from an Iterable. The Iterable will not be iterated until someone calls getRows() and iterates the result, or until someone calls getRowsAsList().
      Parameters:
      rows - rows, each of the same length as signature.size()
      signature - row signature

    • getTableNames

      public Set<String> getTableNames()
      Description copied from interface: DataSource
      Returns the names of all table datasources involved in this query. Does not include names for non-tables, like lookups or inline datasources.

    • getColumnNames

      public List<String> getColumnNames()

    • getColumnTypes

      @Nullable public List<ColumnType> getColumnTypes()

    • getRowsAsList

      public List<Object[]> getRowsAsList()
      Returns rows as a list. If the original Iterable behind this datasource was a List, this method will return it as-is, without copying it. Otherwise, this method will walk the iterable and copy it into a List before returning.

    • getRows

      public Iterable<Object[]> getRows()
      Returns rows as an Iterable.

    • rowsAreArrayList

      public boolean rowsAreArrayList()

    • isCacheable

      public boolean isCacheable(boolean isBroker)
      Description copied from interface: DataSource
      Returns true if queries on this dataSource are cacheable at both the result level and per-segment level. Currently, dataSources that do not actually reference segments (like 'inline'), are not cacheable since cache keys are always based on segment identifiers.

    • isGlobal

      public boolean isGlobal()
      Description copied from interface: DataSource
      Decides if this datasource can be accessed globally.

      This means that all servers have a full copy of this datasource.

      Examples: inline table, lookup.

    • isProcessable

      public boolean isProcessable()
      Description copied from interface: DataSource
      Communicates that this DataSource can be directly used to run a Query.

      A Processable datasource must pack the necessary logic into the DataSource.createSegmentMapFunction(Query).

      Processable examples are: TableDataSource, InlineDataSource, FilteredDataSource. Non-processable ones are those which need further pre-processing before running them. examples are: QueryDataSource and join which are not supported directly.

    • getCacheKey

      public byte[] getCacheKey()
      Description copied from interface: DataSource
      Compute a cache key prefix for a data source. This includes the data sources that participate in the RHS of a join as well as any query specific constructs associated with join data source such as base table filter. This key prefix can be used in segment level cache or result level cache. The function can return following - Non-empty byte array - If there is join datasource involved and caching is possible. The result includes join condition expression, join type and cache key returned by joinable factory for each PreJoinableClause - NULL - There is a join but caching is not possible. It may happen if one of the participating datasource in the JOIN is not cacheable.
      Returns:
      the cache key to be used as part of query cache key

    • getRowSignature

      public RowSignature getRowSignature()
      Returns the row signature (map of column name to type) for this inline datasource. Note that types may be null, meaning we know we have a column with a certain name, but we don't know what its type is.

    • rowAdapter

      public RowAdapter<Object[]> rowAdapter()

    • equals

      public boolean equals(Object o)
      Overrides:
      equals in class Object

    • hashCode

      public int hashCode()
      Overrides:
      hashCode in class Object

    • toString

      public String toString()
      Overrides:
      toString in class Object