// specify a regex operation to split the "document" text lines into a token stream
Fields token = new Fields( "token" );
Fields text = new Fields( "text" );
RegexSplitGenerator splitter = new RegexSplitGenerator( token, "[ \\[\\]\\(\\),.]" );
Fields fieldSelector = new Fields( "doc_id", "token" );
Pipe docPipe = new Each( "token", text, splitter, fieldSelector );
// define "ScrubFunction" to clean up the token stream
Fields scrubArguments = new Fields( "doc_id", "token" );
docPipe = new Each( docPipe, scrubArguments, new ScrubFunction( scrubArguments ), Fields.RESULTS );
// perform a left join to remove stop words, discarding the rows
// which joined with stop words, i.e., were non-null after left join
Pipe stopPipe = new Pipe( "stop" );
Pipe tokenPipe = new HashJoin( docPipe, token, stopPipe, stop, new LeftJoin() );
tokenPipe = new Each( tokenPipe, stop, new RegexFilter( "^$" ) );
tokenPipe = new Retain( tokenPipe, fieldSelector );
// one branch of the flow tallies the token counts for term frequency (TF)
Pipe tfPipe = new Pipe( "TF", tokenPipe );
Fields tf_count = new Fields( "tf_count" );
tfPipe = new CountBy( tfPipe, new Fields( "doc_id", "token" ), tf_count );
Fields tf_token = new Fields( "tf_token" );
tfPipe = new Rename( tfPipe, token, tf_token );
// one branch counts the number of documents (D)
Fields doc_id = new Fields( "doc_id" );
Fields tally = new Fields( "tally" );
Fields rhs_join = new Fields( "rhs_join" );
Fields n_docs = new Fields( "n_docs" );
Pipe dPipe = new Unique( "D", tokenPipe, doc_id );
dPipe = new Each( dPipe, new Insert( tally, 1 ), Fields.ALL );
dPipe = new Each( dPipe, new Insert( rhs_join, 1 ), Fields.ALL );
dPipe = new SumBy( dPipe, rhs_join, tally, n_docs, long.class );
// one branch tallies the token counts for document frequency (DF)
Pipe dfPipe = new Unique( "DF", tokenPipe, Fields.ALL );
Fields df_count = new Fields( "df_count" );
dfPipe = new CountBy( dfPipe, token, df_count );
Fields df_token = new Fields( "df_token" );
Fields lhs_join = new Fields( "lhs_join" );
dfPipe = new Rename( dfPipe, token, df_token );
dfPipe = new Each( dfPipe, new Insert( lhs_join, 1 ), Fields.ALL );
// join to bring together all the components for calculating TF-IDF
// the D side of the join is smaller, so it goes on the RHS
Pipe idfPipe = new HashJoin( dfPipe, lhs_join, dPipe, rhs_join );
// the IDF side of the join is smaller, so it goes on the RHS
Pipe tfidfPipe = new CoGroup( tfPipe, tf_token, idfPipe, df_token );
// calculate the TF-IDF weights, per token, per document
Fields tfidf = new Fields( "tfidf" );
String expression = "(double) tf_count * Math.log( (double) n_docs / ( 1.0 + df_count ) )";
ExpressionFunction tfidfExpression = new ExpressionFunction( tfidf, expression, Double.class );
Fields tfidfArguments = new Fields( "tf_count", "df_count", "n_docs" );
tfidfPipe = new Each( tfidfPipe, tfidfArguments, tfidfExpression, Fields.ALL );
fieldSelector = new Fields( "tf_token", "doc_id", "tfidf" );
tfidfPipe = new Retain( tfidfPipe, fieldSelector );
tfidfPipe = new Rename( tfidfPipe, tf_token, token );
// keep track of the word counts, which are useful for QA
Pipe wcPipe = new Pipe( "wc", tfPipe );
Fields count = new Fields( "count" );
wcPipe = new SumBy( wcPipe, tf_token, tf_count, count, long.class );
wcPipe = new Rename( wcPipe, tf_token, token );