All Classes

Class Summary

Class	Description
CollectionExecutionExample	This example shows how to use the collection based execution of Flink.
CollectionExecutionExample.EMail	POJO for an EMail.
CollectionExecutionExample.User	POJO class representing a user.
ConnectedComponents	An implementation of the connected components algorithm, using a delta iteration.
ConnectedComponents.ComponentIdFilter	Emit the candidate (Vertex-ID, Component-ID) pair if and only if the candidate component ID is less than the vertex's current component ID.
ConnectedComponents.DuplicateValue<T>	Function that turns a value into a 2-tuple where both fields are that value.
ConnectedComponents.NeighborWithComponentIDJoin	UDF that joins a (Vertex-ID, Component-ID) pair that represents the current component that a vertex is associated with, with a (Source-Vertex-ID, Target-VertexID) edge.
ConnectedComponents.UndirectEdge	Undirected edges by emitting for each input edge the input edges itself and an inverted version.
ConnectedComponentsData	Provides the default data sets used for the Connected Components example program.
DataSetDeprecationInfo	The info about the deprecation of DataSet API.
DistCp	A main class of the Flink distcp utility.
EmptyFieldsCountAccumulator	This program filters lines from a CSV file with empty fields.
EmptyFieldsCountAccumulator.EmptyFieldFilter	This function filters all incoming tuples that have one or more empty fields.
EmptyFieldsCountAccumulator.StringTriple	It is recommended to use POJOs (Plain old Java objects) instead of TupleX for data types with many fields.
EmptyFieldsCountAccumulator.VectorAccumulator	This accumulator maintains a vector of counts.
EnumTriangles	Triangle enumeration is a pre-processing step to find closely connected parts in graphs.
EnumTriangles.TupleEdgeConverter	Converts a Tuple2 into an Edge.
EnumTrianglesData	Provides the default data sets used for the Triangle Enumeration example programs.
EnumTrianglesDataTypes	The data classes for EnumTriangles.
EnumTrianglesDataTypes.Edge	A POJO storing two vertex IDs.
EnumTrianglesDataTypes.EdgeWithDegrees	A POJO storing two vertex IDs with degree.
EnumTrianglesDataTypes.Triad	A POJO storing three vertex IDs.
FileCopyTask	A Java POJO that represents a task for copying a single file.
FileCopyTaskInputFormat	An implementation of an input format that dynamically assigns FileCopyTask to the mappers that have finished previously assigned tasks.
FileCopyTaskInputSplit	Implementation of InputSplit for copying files.
KMeans	This example implements a basic K-Means clustering algorithm.
KMeans.Centroid	A simple two-dimensional centroid, basically a point with an ID.
KMeans.CentroidAccumulator	Sums and counts point coordinates.
KMeans.CentroidAverager	Computes new centroid from coordinate sum and count of points.
KMeans.CountAppender	Appends a count variable to the tuple.
KMeans.Point	A simple two-dimensional point.
KMeans.SelectNearestCenter	Determines the closest cluster center for a data point.
KMeansData	Provides the default data sets used for the K-Means example program.
KMeansDataGenerator	Generates data for the KMeans example program.
PageRank	A basic implementation of the Page Rank algorithm using a bulk iteration.
PageRank.BuildOutgoingEdgeList	A reduce function that takes a sequence of edges and builds the adjacency list for the vertex where the edges originate.
PageRank.Dampener	The function that applies the page rank dampening formula.
PageRank.EpsilonFilter	Filter that filters vertices where the rank difference is below a threshold.
PageRank.JoinVertexWithEdgesMatch	Join function that distributes a fraction of a vertex's rank to all neighbors.
PageRank.RankAssigner	A map function that assigns an initial rank to all pages.
PageRankData	Provides the default data sets used for the PageRank example program.
PiEstimation	Estimates the value of Pi using the Monte Carlo method.
PiEstimation.Sampler	Sampler randomly emits points that fall within a square of edge x * y.
PiEstimation.SumReducer	Simply sums up all long values.
TPCHQuery10	This program implements a modified version of the TPC-H query 10.
TPCHQuery3	This program implements a modified version of the TPC-H query 3.
TPCHQuery3.Customer	Customer.
TPCHQuery3.Lineitem	Lineitem.
TPCHQuery3.Order	Order.
TPCHQuery3.ShippingPriorityItem	ShippingPriorityItem.
TransitiveClosureNaive	The transitive closure of a graph contains an edge for each pair of vertices which are endpoints of at least one path in the graph.
WebLogAnalysis	This program processes web logs and relational data.
WebLogAnalysis.AntiJoinVisits	CoGroupFunction that realizes an anti-join.
WebLogAnalysis.FilterByRank	MapFunction that filters for records where the rank exceeds a certain threshold.
WebLogAnalysis.FilterDocByKeyWords	MapFunction that filters for documents that contain a certain set of keywords.
WebLogAnalysis.FilterVisitsByDate	MapFunction that filters for records of the visits relation where the year (from the date string) is equal to a certain value.
WebLogData	Provides the default data sets used for the Weblog Analysis example program.
WebLogDataGenerator	Data generator for the WebLogAnalysis example program.
WordCount	Implements the "WordCount" program that computes a simple word occurrence histogram over text files.
WordCount.Tokenizer	Implements the string tokenizer that splits sentences into words as a user-defined FlatMapFunction.
WordCountData	Provides the default data sets used for the WordCount example program.
WordCountPojo	This example shows an implementation of WordCount without using the Tuple2 type, but a custom class.
WordCountPojo.Tokenizer	Implements the string tokenizer that splits sentences into words as a user-defined FlatMapFunction.
WordCountPojo.Word	This is the POJO (Plain Old Java Object) that is being used for all the operations.