Intro To Cascading

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Introduction to Cascading

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What is Cascading?

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What is Cascading? •abstraction over MapReduce

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What is Cascading? •abstraction over MapReduce • API for data-processing workﬂows

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Why use Cascading?

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Why use Cascading? • MapReduce can be:

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Why use Cascading? • MapReduce can be: • the wrong level of granularity

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Why use Cascading? • MapReduce can be: • the wrong level of granularity • cumbersome to chain together

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Why use Cascading?

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Why use Cascading? • Cascading helps create

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Why use Cascading? • Cascading helps create • higher-level data processing abstractions

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Why use Cascading? • Cascading helps create • higher-level data processing abstractions • sophisticated data pipelines

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Why use Cascading? • Cascading helps create • higher-level data processing abstractions • sophisticated data pipelines • reusable components

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Credits • Cascading writtenby Chris Wensel • based on his users guide http://bit.ly/cascading

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package cascadingtutorial.wordcount; /** *Wordcount example in Cascading */ public class Main { public static void main( String[] args ) { String inputPath = args[0]; String outputPath = args[1]; Scheme inputScheme = new TextLine(new Fields("offset", "line")); Scheme outputScheme = new TextLine(); Tap sourceTap = inputPath.matches( "^[^:]+://.*") ? new Hfs(inputScheme, inputPath) : new Lfs(inputScheme, inputPath); Tap sinkTap = outputPath.matches("^[^:]+://.*") ? new Hfs(outputScheme, outputPath) : new Lfs(outputScheme, outputPath); Pipe wcPipe = new Each("wordcount", new Fields("line"), new RegexSplitGenerator(new Fields("word"), "s+"), new Fields("word")); wcPipe = new GroupBy(wcPipe, new Fields("word")); wcPipe = new Every(wcPipe, new Count(), new Fields("count", "word")); Properties properties = new Properties(); FlowConnector.setApplicationJarClass(properties, Main.class); Flow parsedLogFlow = new FlowConnector(properties) .connect(sourceTap, sinkTap, wcPipe); parsedLogFlow.start(); parsedLogFlow.complete(); } }

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Data Model Pipes Filters

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Data Model ﬁle

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Data Model ﬁle

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Data Model ﬁle

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Data Model ﬁle

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Data Model ﬁle

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Data Model ﬁle

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Data Model file file file

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Data Model file file file Filters

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Tuple

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Pipe Assembly

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Pipe Assembly TupleStream

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Taps: sources &sinks

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Taps: sources &sinks Taps

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Taps: sources &sinks Taps Source

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Taps: sources &sinks Taps Source Sink

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Pipe + Taps= Flow Flow

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Flow Flow Flow Flow Flow

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n Flows Flow Flow Flow Flow Flow

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n Flows =Cascade Flow Flow Flow Flow Flow

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n Flows =Cascade Flow Flow Flow Flow Flow complex

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Example

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import cascading.tap.Tap; import cascading.tuple.Fields; importjava.util.Properties; /** * Wordcount example in Cascading */ public class Main { public static void main( String[] args ) { Scheme inputScheme = new TextLine(new Fields("offset", "line")); Scheme outputScheme = new TextLine(); String inputPath = args[0]; String outputPath = args[1]; Tap sourceTap = inputPath.matches( "^[^:]+://.*") ? new Hfs(inputScheme, inputPath) : new Lfs(inputScheme, inputPath); Tap sinkTap = outputPath.matches("^[^:]+://.*") ? new Hfs(outputScheme, outputPath) : new Lfs(outputScheme, outputPath); Pipe wcPipe = new Each("wordcount", new Fields("line"), new RegexSplitGenerator(new Fields("word"), "s+"), new Fields("word"));

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import cascading.tap.Tap; import cascading.tuple.Fields; importjava.util.Properties; /** * Wordcount example in Cascading */ public class Main { public static void main( String[] args ) { Scheme inputScheme = new TextLine(new Fields("offset", "line")); Scheme outputScheme = new TextLine(); String inputPath = args[0]; String outputPath = args[1]; Tap sourceTap = inputPath.matches( "^[^:]+://.*") ? new Hfs(inputScheme, inputPath) : new Lfs(inputScheme, inputPath); TextLine() Tap sinkTap = outputPath.matches("^[^:]+://.*") ? new Hfs(outputScheme, outputPath) : new Lfs(outputScheme, outputPath); Pipe wcPipe = new Each("wordcount", new Fields("line"), new RegexSplitGenerator(new Fields("word"), "s+"), new Fields("word"));

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import cascading.tap.Tap; import cascading.tuple.Fields; importjava.util.Properties; /** * Wordcount example in Cascading */ public class Main { public static void main( String[] args ) { Scheme inputScheme = new TextLine(new Fields("offset", "line")); Scheme outputScheme = new TextLine(); String inputPath = args[0]; String outputPath = args[1]; Tap sourceTap = inputPath.matches( "^[^:]+://.*") ? new Hfs(inputScheme, inputPath) : new Lfs(inputScheme, inputPath); TextLine() Tap sinkTap SequenceFile() = outputPath.matches("^[^:]+://.*") ? new Hfs(outputScheme, outputPath) : new Lfs(outputScheme, outputPath); Pipe wcPipe = new Each("wordcount", new Fields("line"), new RegexSplitGenerator(new Fields("word"), "s+"), new Fields("word"));

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/** * Wordcountexample in Cascading */ public class Main { public static void main( String[] args ) { Scheme inputScheme = new TextLine(new Fields("offset", "line")); Scheme outputScheme = new TextLine(); String inputPath = args[0]; String outputPath = args[1]; Tap sourceTap = inputPath.matches( "^[^:]+://.*") ? new Hfs(inputScheme, inputPath) : new Lfs(inputScheme, inputPath); Tap sinkTap = outputPath.matches("^[^:]+://.*") ? new Hfs(outputScheme, outputPath) : new Lfs(outputScheme, outputPath); Pipe wcPipe = new Each("wordcount", new Fields("line"), new RegexSplitGenerator(new Fields("word"), "s+"), new Fields("word")); wcPipe = new GroupBy(wcPipe, new Fields("word")); wcPipe = new Every(wcPipe, new Count(), new Fields("count", "word"));

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/** * Wordcountexample in Cascading */ public class Main { hdfs://master0:54310/user/nmurray/data.txt public static void main( String[] args ) { Scheme inputScheme = new TextLine(new Fields("offset", "line")); Scheme outputScheme = new TextLine(); String inputPath = args[0]; String outputPath = args[1]; Tap sourceTap = inputPath.matches( "^[^:]+://.*") ? new Hfs(inputScheme, inputPath) : new Lfs(inputScheme, inputPath); Tap sinkTap = outputPath.matches("^[^:]+://.*") ? new Hfs(outputScheme, outputPath) : new Lfs(outputScheme, outputPath); Pipe wcPipe = new Each("wordcount", new Fields("line"), new RegexSplitGenerator(new Fields("word"), "s+"), new Fields("word")); wcPipe = new GroupBy(wcPipe, new Fields("word")); wcPipe = new Every(wcPipe, new Count(), new Fields("count", "word"));

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/** * Wordcountexample in Cascading */ public class Main { hdfs://master0:54310/user/nmurray/data.txt new Hfs() public static void main( String[] args ) { Scheme inputScheme = new TextLine(new Fields("offset", "line")); Scheme outputScheme = new TextLine(); String inputPath = args[0]; String outputPath = args[1]; Tap sourceTap = inputPath.matches( "^[^:]+://.*") ? new Hfs(inputScheme, inputPath) : new Lfs(inputScheme, inputPath); Tap sinkTap = outputPath.matches("^[^:]+://.*") ? new Hfs(outputScheme, outputPath) : new Lfs(outputScheme, outputPath); Pipe wcPipe = new Each("wordcount", new Fields("line"), new RegexSplitGenerator(new Fields("word"), "s+"), new Fields("word")); wcPipe = new GroupBy(wcPipe, new Fields("word")); wcPipe = new Every(wcPipe, new Count(), new Fields("count", "word"));

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/** * Wordcountexample in Cascading */ public class Main { hdfs://master0:54310/user/nmurray/data.txt new Hfs() data/sources/obama-inaugural-address.txt public static void main( String[] args ) { Scheme inputScheme = new TextLine(new Fields("offset", "line")); Scheme outputScheme = new TextLine(); String inputPath = args[0]; String outputPath = args[1]; Tap sourceTap = inputPath.matches( "^[^:]+://.*") ? new Hfs(inputScheme, inputPath) : new Lfs(inputScheme, inputPath); Tap sinkTap = outputPath.matches("^[^:]+://.*") ? new Hfs(outputScheme, outputPath) : new Lfs(outputScheme, outputPath); Pipe wcPipe = new Each("wordcount", new Fields("line"), new RegexSplitGenerator(new Fields("word"), "s+"), new Fields("word")); wcPipe = new GroupBy(wcPipe, new Fields("word")); wcPipe = new Every(wcPipe, new Count(), new Fields("count", "word"));

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/** * Wordcountexample in Cascading */ public class Main { hdfs://master0:54310/user/nmurray/data.txt new Hfs() data/sources/obama-inaugural-address.txt public static void main( String[] args ) new Lfs() { Scheme inputScheme = new TextLine(new Fields("offset", "line")); Scheme outputScheme = new TextLine(); String inputPath = args[0]; String outputPath = args[1]; Tap sourceTap = inputPath.matches( "^[^:]+://.*") ? new Hfs(inputScheme, inputPath) : new Lfs(inputScheme, inputPath); Tap sinkTap = outputPath.matches("^[^:]+://.*") ? new Hfs(outputScheme, outputPath) : new Lfs(outputScheme, outputPath); Pipe wcPipe = new Each("wordcount", new Fields("line"), new RegexSplitGenerator(new Fields("word"), "s+"), new Fields("word")); wcPipe = new GroupBy(wcPipe, new Fields("word")); wcPipe = new Every(wcPipe, new Count(), new Fields("count", "word"));

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/** * Wordcountexample in Cascading */ public class Main { hdfs://master0:54310/user/nmurray/data.txt new Hfs() data/sources/obama-inaugural-address.txt public static void main( String[] args ) new Lfs() { Scheme inputScheme = new TextLine(new Fields("offset", "line")); Scheme outputScheme = new TextLine(); String inputPath = args[0]; String outputPath = args[1]; Tap sourceTap = inputPath.matches( "^[^:]+://.*") ? new Hfs(inputScheme, inputPath) : new Lfs(inputScheme, inputPath); Tap sinkTap = outputPath.matches("^[^:]+://.*") ? new Hfs(outputScheme, outputPath) : new Lfs(outputScheme, outputPath); Pipe wcPipe = new Each("wordcount", new Fields("line"), S3fs() new RegexSplitGenerator(new Fields("word"), "s+"), new Fields("word")); wcPipe = new GroupBy(wcPipe, new Fields("word")); wcPipe = new Every(wcPipe, new Count(), new Fields("count", "word"));

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/** * Wordcountexample in Cascading */ public class Main { hdfs://master0:54310/user/nmurray/data.txt new Hfs() data/sources/obama-inaugural-address.txt public static void main( String[] args ) new Lfs() { Scheme inputScheme = new TextLine(new Fields("offset", "line")); Scheme outputScheme = new TextLine(); String inputPath = args[0]; String outputPath = args[1]; Tap sourceTap = inputPath.matches( "^[^:]+://.*") ? new Hfs(inputScheme, inputPath) : new Lfs(inputScheme, inputPath); Tap sinkTap = outputPath.matches("^[^:]+://.*") ? new Hfs(outputScheme, outputPath) : new Lfs(outputScheme, outputPath); Pipe wcPipe = new Each("wordcount", new Fields("line"), S3fs() new RegexSplitGenerator(new Fields("word"), "s+"), new Fields("word")); GlobHfs() new Fields("count", "word")); wcPipe = new GroupBy(wcPipe, new Fields("word")); wcPipe = new Every(wcPipe, new Count(),

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/** * Wordcountexample in Cascading */ public class Main { public static void main( String[] args ) { Scheme inputScheme = new TextLine(new Fields("offset", "line")); Scheme outputScheme = new TextLine(); String inputPath = args[0]; String outputPath = args[1]; Tap sourceTap = inputPath.matches( "^[^:]+://.*") ? new Hfs(inputScheme, inputPath) : new Lfs(inputScheme, inputPath); Tap sinkTap = outputPath.matches("^[^:]+://.*") ? new Hfs(outputScheme, outputPath) : new Lfs(outputScheme, outputPath); Pipe wcPipe = new Each("wordcount", new Fields("line"), new RegexSplitGenerator(new Fields("word"), "s+"), new Fields("word")); wcPipe = new GroupBy(wcPipe, new Fields("word")); wcPipe = new Every(wcPipe, new Count(), new Fields("count", "word"));

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Scheme outputScheme =new TextLine(); String inputPath = args[0]; String outputPath = args[1]; Tap sourceTap = inputPath.matches( "^[^:]+://.*") ? new Hfs(inputScheme, inputPath) : new Lfs(inputScheme, inputPath); Tap sinkTap = outputPath.matches("^[^:]+://.*") ? new Hfs(outputScheme, outputPath) : new Lfs(outputScheme, outputPath); Pipe wcPipe = new Each("wordcount", new Fields("line"), new RegexSplitGenerator(new Fields("word"), "s+"), new Fields("word")); wcPipe = new GroupBy(wcPipe, new Fields("word")); wcPipe = new Every(wcPipe, new Count(), new Fields("count", "word")); Properties properties = new Properties(); FlowConnector.setApplicationJarClass(properties, Main.class); Flow parsedLogFlow = new FlowConnector(properties) .connect(sourceTap, sinkTap, wcPipe); parsedLogFlow.start(); parsedLogFlow.complete(); } }

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Scheme outputScheme =new TextLine(); String inputPath = args[0]; String outputPath = args[1]; Pipe Assembly Tap sourceTap = inputPath.matches( "^[^:]+://.*") ? new Hfs(inputScheme, inputPath) : new Lfs(inputScheme, inputPath); Tap sinkTap = outputPath.matches("^[^:]+://.*") ? new Hfs(outputScheme, outputPath) : new Lfs(outputScheme, outputPath); Pipe wcPipe = new Each("wordcount", new Fields("line"), new RegexSplitGenerator(new Fields("word"), "s+"), new Fields("word")); wcPipe = new GroupBy(wcPipe, new Fields("word")); wcPipe = new Every(wcPipe, new Count(), new Fields("count", "word")); Properties properties = new Properties(); FlowConnector.setApplicationJarClass(properties, Main.class); Flow parsedLogFlow = new FlowConnector(properties) .connect(sourceTap, sinkTap, wcPipe); parsedLogFlow.start(); parsedLogFlow.complete(); } }

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Pipe Assemblies

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Pipe Assemblies

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Pipe Assemblies • Deﬁnework against a Tuple Stream

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Pipe Assemblies • Deﬁnework against a Tuple Stream • May have multiple sources and sinks

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Pipe Assemblies • Deﬁnework against a Tuple Stream • May have multiple sources and sinks • Splits

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Pipe Assemblies • Deﬁnework against a Tuple Stream • May have multiple sources and sinks • Splits • Merges

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Pipe Assemblies • Deﬁnework against a Tuple Stream • May have multiple sources and sinks • Splits • Merges • Joins

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Pipe Assemblies

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Pipe Assemblies • Pipe

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Pipe Assemblies • Pipe • Each • GroupBy • CoGroup • Every • SubAssembly

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Pipe Assemblies • Pipe Applies a • Each Function or Filter • GroupBy Operation to each • CoGroup Tuple • Every • SubAssembly

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Pipe Assemblies • Pipe • Each Group • GroupBy (& merge) • CoGroup • Every • SubAssembly

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Pipe Assemblies • Pipe • Each • GroupBy Joins • CoGroup (inner, outer, left, right) • Every • SubAssembly

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Pipe Assemblies • Pipe • Each • GroupBy • CoGroup • Every Applies an Aggregator (count, sum) to every group of Tuples. • SubAssembly

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Pipe Assemblies • Pipe • Each • GroupBy • CoGroup • Every • SubAssembly Nesting

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Each vs. Every

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Each vs. Every •Each() is for individual Tuples

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Each vs. Every •Each() is for individual Tuples • Every() is for groups of Tuples

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Each new Each(previousPipe, argumentSelector, operation, outputSelector)

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Each new Each(previousPipe, argumentSelector, operation, outputSelector) Pipe wcPipe = new Each("wordcount", new Fields("line"), new RegexSplitGenerator(new Fields("word"), "s+"), new Fields("word"));

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Each new Each(previousPipe, argumentSelector, operation, outputSelector) Pipe wcPipe = new Each("wordcount", new Fields("line"), new RegexSplitGenerator(new Fields("word"), "s+"), new Fields("word")); Fields()

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Each offset line 0 the lazy brown fox Pipe wcPipe = new Each("wordcount", new Fields("line"), new RegexSplitGenerator(new Fields("word"), "s+"), new Fields("word"));

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Each offset line 0 the lazy brown fox Pipe wcPipe = new Each("wordcount", new Fields("line"), new RegexSplitGenerator(new Fields("word"), "s+"), new Fields("word"));

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Each X offset 0 line the lazy brown fox Pipe wcPipe = new Each("wordcount", new Fields("line"), new RegexSplitGenerator(new Fields("word"), "s+"), new Fields("word"));

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Each X offset 0 line the lazy brown fox Pipe wcPipe = new Each("wordcount", new Fields("line"), new RegexSplitGenerator(new Fields("word"), "s+"), new Fields("word")); word word word word the lazy brown fox

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Operations: Functions

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Operations: Functions • Insert()

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Operations: Functions • Insert() • RegexParser() / RegexGenerator() / RegexReplace()

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Operations: Functions • Insert() • RegexParser() / RegexGenerator() / RegexReplace() • DateParser() / DateFormatter()

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Operations: Functions • Insert() • RegexParser() / RegexGenerator() / RegexReplace() • DateParser() / DateFormatter() • XPathGenerator()

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Operations: Functions • Insert() • RegexParser() / RegexGenerator() / RegexReplace() • DateParser() / DateFormatter() • XPathGenerator() • Identity()

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Operations: Functions • Insert() • RegexParser() / RegexGenerator() / RegexReplace() • DateParser() / DateFormatter() • XPathGenerator() • Identity() • etc...

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Operations: Filters

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Operations: Filters • RegexFilter()

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Operations: Filters • RegexFilter() • FilterNull()

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Operations: Filters • RegexFilter() • FilterNull() • And() / Or() / Not() / Xor()

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Operations: Filters • RegexFilter() • FilterNull() • And() / Or() / Not() / Xor() • ExpressionFilter()

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Operations: Filters • RegexFilter() • FilterNull() • And() / Or() / Not() / Xor() • ExpressionFilter() • etc...

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Each Pipe wcPipe = newEach("wordcount", new Fields("line"), new RegexSplitGenerator(new Fields("word"), "s+"), new Fields("word"));

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String inputPath =args[0]; String outputPath = args[1]; Tap sourceTap = inputPath.matches( "^[^:]+://.*") ? new Hfs(inputScheme, inputPath) : new Lfs(inputScheme, inputPath); Tap sinkTap = outputPath.matches("^[^:]+://.*") ? new Hfs(outputScheme, outputPath) : new Lfs(outputScheme, outputPath); Pipe wcPipe = new Each("wordcount", new Fields("line"), new RegexSplitGenerator(new Fields("word"), "s+"), new Fields("word")); wcPipe = new GroupBy(wcPipe, new Fields("word")); wcPipe = new Every(wcPipe, new Count(), new Fields("count", "word")); Properties properties = new Properties(); FlowConnector.setApplicationJarClass(properties, Main.class); Flow parsedLogFlow = new FlowConnector(properties) .connect(sourceTap, sinkTap, wcPipe); parsedLogFlow.start(); parsedLogFlow.complete(); } }

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new Lfs(inputScheme, inputPath); Tap sinkTap = outputPath.matches("^[^:]+://.*") ? new Hfs(outputScheme, outputPath) : new Lfs(outputScheme, outputPath); Pipe wcPipe = new Each("wordcount", new Fields("line"), new RegexSplitGenerator(new Fields("word"), "s+"), new Fields("word")); wcPipe = new GroupBy(wcPipe, new Fields("word")); wcPipe = new Every(wcPipe, new Count(), new Fields("count", "word")); Properties properties = new Properties(); FlowConnector.setApplicationJarClass(properties, Main.class); Flow parsedLogFlow = new FlowConnector(properties) .connect(sourceTap, sinkTap, wcPipe); parsedLogFlow.start(); parsedLogFlow.complete(); } }

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Every new Every(previousPipe, argumentSelector, operation, outputSelector)

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Every new Every(previousPipe, argumentSelector, operation, outputSelector) new Every(wcPipe, new Count(), new Fields("count", "word"));

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new Every(wcPipe, newCount(), new Fields("count", "word"));

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Operations: Aggregator

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Operations: Aggregator • Average()

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Operations: Aggregator • Average() • Count()

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Operations: Aggregator • Average() • Count() • First() / Last()

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Operations: Aggregator • Average() • Count() • First() / Last() • Min() / Max()

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Operations: Aggregator • Average() • Count() • First() / Last() • Min() / Max() • Sum()

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Every new Every(previousPipe, argumentSelector, operation, outputSelector)

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Every new Every(previousPipe, argumentSelector, operation, outputSelector) new Every(wcPipe, new Count(), new Fields("count", "word"));

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Every new Every(previousPipe, argumentSelector, operation, outputSelector) new Every(wcPipe, new Count(), new Fields("count", "word")); new Every(wcPipe, Fields.ALL, new Count(), new Fields("count", "word"));

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Field Selection

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Predefined Field Sets

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Predefined Field Sets Fields.ALL all available fields Fields.GROUP fields used for last grouping Fields.VALUES fields not used for last grouping fields of argument Tuple Fields.ARGS (for Operations) replaces input with Operation result Fields.RESULTS (for Pipes)

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Field Selection new Each(previousPipe, argumentSelector, operation, outputSelector) pipe = new Each(pipe, new Fields("timestamp"), new DateParser("yyyy-MM-dd HH:mm:ss"), new Fields("timestamp"));

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Field Selection new Each(previousPipe, argumentSelector, operation, outputSelector) Operation Input Tuple = Original Tuple Argument Selector

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Field Selection pipe =new Each(pipe, new Fields("timestamp"), new DateParser("yyyy-MM-dd HH:mm:ss"), new Fields("ts", "search_term", "visitor_id"));

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Field Selection Original Tuple visitor_ search_ time page_ id id term stamp number pipe = new Each(pipe, new Fields("timestamp"), new DateParser("yyyy-MM-dd HH:mm:ss"), new Fields("ts", "search_term", "visitor_id"));

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Field Selection Original Tuple Argument Selector visitor_ search_ time page_ id timestamp id term stamp number pipe = new Each(pipe, new Fields("timestamp"), new DateParser("yyyy-MM-dd HH:mm:ss"), new Fields("ts", "search_term", "visitor_id"));

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Field Selection Original Tuple Argument Selector visitor_ search_ time page_ id timestamp id term stamp number pipe = new Each(pipe, new Fields("timestamp"), new DateParser("yyyy-MM-dd HH:mm:ss"), new Fields("ts", "search_term", "visitor_id"));

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Field Selection Original Tuple Argument Selector visitor_ search_ time page_ id timestamp id term stamp number pipe = new Each(pipe, new Fields("timestamp"), new DateParser("yyyy-MM-dd HH:mm:ss"), new Fields("ts", "search_term", "visitor_id")); Input to DateParser will be: timestamp

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Field Selection new Each(previousPipe, argumentSelector, operation, outputSelector) Output Tuple = Original Tuple ⊕ Operation Tuple Output Selector

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Field Selection pipe =new Each(pipe, new Fields("timestamp"), new DateParser("yyyy-MM-dd HH:mm:ss"), new Fields("ts", "search_term", "visitor_id"));

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Field Selection Original Tuple visitor_ search_ time page_ id id term stamp number pipe = new Each(pipe, new Fields("timestamp"), new DateParser("yyyy-MM-dd HH:mm:ss"), new Fields("ts", "search_term", "visitor_id"));

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Field Selection Original Tuple id visitor_ id search_ term time stamp page_ number ⊕ pipe = new Each(pipe, new Fields("timestamp"), new DateParser("yyyy-MM-dd HH:mm:ss"), new Fields("ts", "search_term", "visitor_id"));

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Field Selection Original Tuple DateParser Output id visitor_ id search_ term time stamp page_ number ⊕ ts pipe = new Each(pipe, new Fields("timestamp"), new DateParser("yyyy-MM-dd HH:mm:ss"), new Fields("ts", "search_term", "visitor_id"));

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Field Selection Original Tuple DateParser Output Output Selector id visitor_ id search_ term time stamp page_ number ⊕ ts ts search_ term visitor_ id pipe = new Each(pipe, new Fields("timestamp"), new DateParser("yyyy-MM-dd HH:mm:ss"), new Fields("ts", "search_term", "visitor_id"));

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Field Selection Original Tuple DateParser Output Output Selector id visitor_ id search_ term time stamp page_ number ⊕ ts ts search_ term visitor_ id pipe = new Each(pipe, new Fields("timestamp"), new DateParser("yyyy-MM-dd HH:mm:ss"), new Fields("ts", "search_term", "visitor_id")); Output of Each will be: search_ visitor_ ts term id

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Field Selection Original Tuple DateParser Output Output Selector X id visitor_ id search_ term XX ⊕ time stamp page_ number ts ts search_ term visitor_ id pipe = new Each(pipe, new Fields("timestamp"), new DateParser("yyyy-MM-dd HH:mm:ss"), new Fields("ts", "search_term", "visitor_id")); Output of Each will be: search_ visitor_ ts term id

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word hello word hello word world new Every(wcPipe, new Count(), new Fields("count", "word"));

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word hello word hello word world new Every(wcPipe, new Count(), new Fields("count", "word")); count word 2 hello count word 1 world

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new Lfs(outputScheme, outputPath); Pipe wcPipe = new Each("wordcount", new Fields("line"), new RegexSplitGenerator(new Fields("word"), "s+"), new Fields("word")); wcPipe = new GroupBy(wcPipe, new Fields("word")); wcPipe = new Every(wcPipe, new Count(), new Fields("count", "word")); Properties properties = new Properties(); FlowConnector.setApplicationJarClass(properties, Main.class); Flow parsedLogFlow = new FlowConnector(properties) .connect(sourceTap, sinkTap, wcPipe); parsedLogFlow.start(); parsedLogFlow.complete(); } }

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Run

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input: mary had a little lamb little lamb little lamb mary had a little lamb whose fleece was white as snow

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input: mary had a little lamb little lamb little lamb mary had a little lamb whose fleece was white as snow command: hadoop jar ./target/cascading-tutorial-1.0.0.jar data/sources/misc/mary.txt data/output

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output: 2 a 1 as 1 fleece 2 had 4 lamb 4 little 2 mary 1 snow 1 was 1 white 1 whose

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What’s next?

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apply operations to tuple streams

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apply operations to tuple streams repeat.

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Cookbook

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Cookbook // remove alltuples where search_term is '-' pipe = new Each(pipe, new Fields("search_term"), new RegexFilter("^(-)$", true));

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Cookbook // convert "timestamp"String field to "ts" long field pipe = new Each(pipe, new Fields("timestamp"), new DateParser("yyyy-MM-dd HH:mm:ss"), Fields.ALL);

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Cookbook // td -timestamp of day-level granularity pipe = new Each(pipe, new Fields("ts"), new ExpressionFunction( new Fields("td"), "ts - (ts % (24 * 60 * 60 * 1000))", long.class), Fields.ALL);

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Cookbook // SELECT DISTINCTvisitor_id // GROUP BY visitor_id ORDER BY ts pipe = new GroupBy(pipe, new Fields("visitor_id"), new Fields("ts")); // take the First() tuple of every grouping pipe = new Every(pipe, Fields.ALL, new First(), Fields.RESULTS);

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Custom Operations

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Desired Operation Pipe pipe= new Each("ngram pipe", new Fields("line"), new NGramTokenizer(2), new Fields("ngram"));

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Desired Operation line mary had a little lamb Pipe pipe = new Each("ngram pipe", new Fields("line"), new NGramTokenizer(2), new Fields("ngram"));

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Desired Operation line mary had a little lamb Pipe pipe = new Each("ngram pipe", new Fields("line"), new NGramTokenizer(2), new Fields("ngram")); ngram mary had

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Desired Operation line mary had a little lamb Pipe pipe = new Each("ngram pipe", new Fields("line"), new NGramTokenizer(2), new Fields("ngram")); ngram ngram mary had had a

175.
Desired Operation line mary had a little lamb Pipe pipe = new Each("ngram pipe", new Fields("line"), new NGramTokenizer(2), new Fields("ngram")); ngram ngram ngram mary had had a a little

176.
Desired Operation line mary had a little lamb Pipe pipe = new Each("ngram pipe", new Fields("line"), new NGramTokenizer(2), new Fields("ngram")); ngram ngram ngram ngram mary had had a a little little lamb

177.
Custom Operations

178.
Custom Operations • extendBaseOperation

179.
Custom Operations • extendBaseOperation • implement Function (or Filter)

180.
Custom Operations • extendBaseOperation • implement Function (or Filter) • implement operate

181.
public class NGramTokenizerextends BaseOperation implements Function { private int size; public NGramTokenizer(int size) { super(new Fields("ngram")); this.size = size; } public void operate(FlowProcess flowProcess, FunctionCall functionCall) { String token; TupleEntry arguments = functionCall.getArguments(); com.attinteractive.util.NGramTokenizer t = new com.attinteractive.util.NGramTokenizer(arguments.getString(0), this.size); while((token = t.next()) != null) { TupleEntry result = new TupleEntry(new Fields("ngram"), new Tuple(token)); functionCall.getOutputCollector().add(result); } } }

182.

183.

184.

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186.

187.

188.

189.
Tuple 123 vis-abc tacos 2009-10-08 03:21:23 1

190.
Tuple 123 vis-abc tacos 2009-10-08 03:21:23 1 zero-indexed, ordered values

191.
Tuple 123 vis-abc tacos 2009-10-08 03:21:23 1 Fields id visitor_ search_ id term time stamp page_ number list of strings representing field names

192.
Tuple 123 vis-abc tacos 2009-10-08 03:21:23 1 Fields id visitor_ search_ id term time stamp page_ number

193.
TupleEntry visitor_ search_ time page_ id id term stamp number 123 vis-abc tacos 2009-10-08 03:21:23 1

194.

195.

196.

197.
Success line mary had a little lamb Pipe pipe = new Each("ngram pipe", new Fields("line"), new NGramTokenizer(2), new Fields("ngram")); ngram ngram ngram ngram mary had had a a little little lamb

198.
code examples

199.
dot

200.
dot Flow importFlow =flowConnector.connect(sourceTap, tmpIntermediateTap, importPipe); importFlow.writeDOT( "import-flow.dot" );

204.
What next?

205.
What next?

206.
What next? • http://www.cascading.org/

207.
What next? • http://www.cascading.org/ •http://bit.ly/cascading

208.
Questions? <nmurray@att.com>

Intro To Cascading

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