Package org.apache.solr.client.solrj.io.stream

Interface ParallelMetricsRollup

All Known Implementing Classes:

FacetStream, StatsStream

public interface ParallelMetricsRollup

Indicates the underlying stream source supports parallelizing metrics computation across collections using a rollup of metrics from each collection.

Method Summary

Modifier and Type	Method	Description
default Optional<Metric[]>	getRollupMetrics(Metric[] metrics)	Either an array of metrics that can be parallelized and rolled up or empty.
TupleStream	getSortedRollupStream(ParallelListStream plistStream, Metric[] rollupMetrics)	Get the rollup for the parallelized streams that is sorted based on the original (non-parallel) sort order.
default Optional<TupleStream>	openParallelStream(StreamContext context, List<String> partitions, Metric[] metrics)	Given a list of partitions (collections), open a select stream that projects the dimensions and metrics produced by rolling up over a parallelized group of streams.
TupleStream[]	parallelize(List<String> partitions)	Given a list of collections, return an array of TupleStream for each partition.

Method Details

parallelize

TupleStream[] parallelize(List<String> partitions)
                   throws IOException

Given a list of collections, return an array of TupleStream for each partition.

Parameters:

partitions - A list of collections to parallelize metrics computation across.

Returns:

An array of TupleStream for each partition requested.

Throws:

IOException - if an error occurs while constructing the underlying TupleStream for a partition.

getSortedRollupStream

TupleStream getSortedRollupStream(ParallelListStream plistStream,
 Metric[] rollupMetrics)
                           throws IOException

Get the rollup for the parallelized streams that is sorted based on the original (non-parallel) sort order.

Parameters:

plistStream - A parallel list stream to fetch metrics from each partition concurrently

rollupMetrics - An array of metrics to rollup

Returns:

A rollup over parallelized streams that provide metrics; this is typically a SortStream.

Throws:

IOException - if an error occurs while reading from the sorted stream

openParallelStream

default Optional<TupleStream> openParallelStream(StreamContext context,
 List<String> partitions,
 Metric[] metrics)
                                          throws IOException

Given a list of partitions (collections), open a select stream that projects the dimensions and metrics produced by rolling up over a parallelized group of streams. If it's not possible to rollup the metrics produced by the underlying metrics stream, this method returns Optional.empty.

Parameters:

context - The current streaming expression context

partitions - A list of collections to parallelize metrics computation across.

metrics - A list of metrics to rollup.

Returns:

Either a TupleStream that performs a rollup over parallelized streams or empty if parallelization is not possible.

Throws:

IOException - if an error occurs reading tuples from the parallelized streams

getRollupMetrics

default Optional<Metric[]> getRollupMetrics(Metric[] metrics)

Either an array of metrics that can be parallelized and rolled up or empty.

Parameters:

metrics - The list of metrics that we want to parallelize.

Returns:

Either an array of metrics that can be parallelized and rolled up or empty.