How to delete volatile layer data

The Data Client Library provides the class LayerUpdater to perform update
operations on volatile layers.

The LayerUpdater has 3 methods:

updateLayer(catalogHrn, layerId) defines the catalog and layer which should
be updated.
option(key, value) can be used to specify if only the data should be deleted
while the metadata is kept by setting "olp.volatile.delete-data-only" to
true. By default both, metadata and data are deleted.
delete(queryString) performs the delete operation according the query
string. The query string is in RSQL format. The delete function
call is blocking/synchronous. It returns when the delete operation finished.

Project dependencies

If you want to create an application that uses the HERE platform Spark Connector
to delete data from volatile layer, add the required dependencies to your
project as described in chapter
Dependencies for Spark Connector.

Examples

The following snippet demonstrates how to delete data from a volatile layer of a
catalog.

import com.here.platform.data.client.spark.LayerDataFrameReader.SparkSessionExt
import org.apache.spark.sql.SparkSession
val df = sparkSession
  .updateLayer(catalogHrn, layerId)
  .delete(s"mt_partition=in=($partitionId, $anotherPartitionId)")

val deleteResult = df.select("result").first().getString(0)
val deletedCount = df.select("count").first().getInt(0)
val deletionMessage = df.select("message").first().getString(0)

import static org.apache.spark.sql.functions.*;

import com.here.hrn.HRN;
import com.here.platform.data.client.spark.javadsl.JavaLayerUpdater;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.SparkSession;
import org.apache.spark.sql.types.IntegerType;
Dataset<Row> dataFrame =
    JavaLayerUpdater.create(sparkSession)
        .updateLayer(catalogHrn, layerId)
        .delete(String.format("mt_partition=in=(%s,%s)", partitionId, anotherPartitionId));

String deleteResult = dataFrame.select("result").first().getString(0);
int deletedCount = dataFrame.select("count").first().getInt(0);
String deletionMessage = dataFrame.select("message").first().getString(0);

Note

For information on RSQL, see RSQL.