Uses of Class
org.apache.flink.runtime.scheduler.adaptivebatch.BlockingInputInfo

Packages that use BlockingInputInfo

Package	Description
org.apache.flink.runtime.scheduler.adaptivebatch
org.apache.flink.runtime.scheduler.adaptivebatch.util

Uses of BlockingInputInfo in org.apache.flink.runtime.scheduler.adaptivebatch

Method parameters in org.apache.flink.runtime.scheduler.adaptivebatch with type arguments of type BlockingInputInfo

Modifier and Type	Method	Description
ParallelismAndInputInfos	DefaultVertexParallelismAndInputInfosDecider.decideParallelismAndInputInfosForVertex(JobVertexID jobVertexId, List<BlockingInputInfo> consumedResults, int vertexInitialParallelism, int vertexMinParallelism, int vertexMaxParallelism)
ParallelismAndInputInfos	VertexParallelismAndInputInfosDecider.decideParallelismAndInputInfosForVertex(JobVertexID jobVertexId, List<BlockingInputInfo> consumedResults, int vertexInitialParallelism, int vertexMinParallelism, int vertexMaxParallelism)	Decide the parallelism and JobVertexInputInfos for this job vertex.

Uses of BlockingInputInfo in org.apache.flink.runtime.scheduler.adaptivebatch.util

Methods in org.apache.flink.runtime.scheduler.adaptivebatch.util that return types with arguments of type BlockingInputInfo

Modifier and Type	Method	Description
static List<BlockingInputInfo>	VertexParallelismAndInputInfosDeciderUtils.getNonBroadcastInputInfos(List<BlockingInputInfo> consumedResults)

Methods in org.apache.flink.runtime.scheduler.adaptivebatch.util with parameters of type BlockingInputInfo

Modifier and Type	Method	Description
static JobVertexInputInfo	VertexParallelismAndInputInfosDeciderUtils.createdJobVertexInputInfoForBroadcast(BlockingInputInfo inputInfo, int parallelism)
static JobVertexInputInfo	VertexParallelismAndInputInfosDeciderUtils.createdJobVertexInputInfoForNonBroadcast(BlockingInputInfo inputInfo, List<IndexRange> subpartitionSliceRanges, List<SubpartitionSlice> subpartitionSlices)
static void	VertexParallelismAndInputInfosDeciderUtils.logBalancedDataDistributionOptimizationResult(org.slf4j.Logger logger, JobVertexID jobVertexId, BlockingInputInfo inputInfo, JobVertexInputInfo optimizedJobVertexInputInfo)	Logs the data distribution optimization info when a balanced data distribution algorithm is effectively optimized compared to the num-based data distribution algorithm.

Method parameters in org.apache.flink.runtime.scheduler.adaptivebatch.util with type arguments of type BlockingInputInfo

Modifier and Type	Method	Description
static long	VertexParallelismAndInputInfosDeciderUtils.calculateDataVolumePerTaskForInputsGroup(long globalDataVolumePerTask, List<BlockingInputInfo> inputsGroup, List<BlockingInputInfo> allInputs)
static boolean	VertexParallelismAndInputInfosDeciderUtils.checkAndGetIntraCorrelation(List<BlockingInputInfo> inputInfos)
static int	VertexParallelismAndInputInfosDeciderUtils.checkAndGetSubpartitionNum(List<BlockingInputInfo> consumedResults)
Map<IntermediateDataSetID,JobVertexInputInfo>	AllToAllVertexInputInfoComputer.compute(JobVertexID jobVertexId, List<BlockingInputInfo> inputInfos, int parallelism, int minParallelism, int maxParallelism, long dataVolumePerTask)	Decide parallelism and input infos, which will make the data be evenly distributed to downstream subtasks for ALL_TO_ALL, such that different downstream subtasks consume roughly the same amount of data.
Map<IntermediateDataSetID,JobVertexInputInfo>	PointwiseVertexInputInfoComputer.compute(List<BlockingInputInfo> inputInfos, int parallelism, int minParallelism, int maxParallelism, long dataVolumePerTask)	Decide parallelism and input infos, which will make the data be evenly distributed to downstream subtasks for POINTWISE, such that different downstream subtasks consume roughly the same amount of data.
static AggregatedBlockingInputInfo	AggregatedBlockingInputInfo.createAggregatedBlockingInputInfo(long defaultSkewedThreshold, double skewedFactor, long dataVolumePerTask, List<BlockingInputInfo> inputInfos)
static Map<IntermediateDataSetID,JobVertexInputInfo>	VertexParallelismAndInputInfosDeciderUtils.createJobVertexInputInfos(List<BlockingInputInfo> inputInfos, Map<Integer,List<SubpartitionSlice>> subpartitionSlices, List<IndexRange> subpartitionSliceRanges, Function<Integer,Integer> subpartitionSliceKeyResolver)
static int	VertexParallelismAndInputInfosDeciderUtils.getMaxNumPartitions(List<BlockingInputInfo> consumedResults)
static List<BlockingInputInfo>	VertexParallelismAndInputInfosDeciderUtils.getNonBroadcastInputInfos(List<BlockingInputInfo> consumedResults)
static boolean	VertexParallelismAndInputInfosDeciderUtils.hasSameNumPartitions(List<BlockingInputInfo> inputInfos)