I like to generate multiple tuples from a single tuple. What I mean is: I have file with following data in it.
>> cat data
ID | ColumnName1:Value1 | C
Here is the UDF version. I prefer to return a BAG:
import java.io.IOException;
import org.apache.pig.EvalFunc;
import org.apache.pig.backend.executionengine.ExecException;
import org.apache.pig.data.BagFactory;
import org.apache.pig.data.DataBag;
import org.apache.pig.data.DataType;
import org.apache.pig.data.Tuple;
import org.apache.pig.data.TupleFactory;
import org.apache.pig.impl.logicalLayer.FrontendException;
import org.apache.pig.impl.logicalLayer.schema.Schema;
/**
* Converts input chararray "ID|ColumnName1:Value1|ColumnName2:Value2|.." into a bag
* {(ID, ColumnName1, Value1), (ID, ColumnName2, Value2), ...}
*
* Default rows separator is '|' and key value separator is ':'.
* In this implementation white spaces around separator characters are not removed.
* ID can be made of any character (including sequence of white spaces).
* @author
*
*/
public class TupleToBagColumnValuePairs extends EvalFunc<DataBag> {
private static final TupleFactory tupleFactory = TupleFactory.getInstance();
private static final BagFactory bagFactory = BagFactory.getInstance();
//Row separator character. Default is '|'.
private String rowsSeparator;
//Column value separator character. Default i
private String columnValueSeparator;
public TupleToBagColumnValuePairs() {
this.rowsSeparator = "\\|";
this.columnValueSeparator = ":";
}
public TupleToBagColumnValuePairs(String rowsSeparator, String keyValueSeparator) {
this.rowsSeparator = rowsSeparator;
this.columnValueSeparator = keyValueSeparator;
}
/**
* Creates a tuple with 3 fields (id:chararray, column:chararray, value:chararray)
* @param outputBag Output tuples (id, column, value) are added to this bag
* @param id
* @param column
* @param value
* @throws ExecException
*/
protected void addTuple(DataBag outputBag, String id, String column, String value) throws ExecException {
Tuple outputTuple = tupleFactory.newTuple();
outputTuple.append(id);
outputTuple.append(column);
outputTuple.append( value);
outputBag.add(outputTuple);
}
/**
* Takes column{separator}value from splitInputLine, splits id into column value and adds them to the outputBag as (id, column, value)
* @param outputBag Output tuples (id, column, value) should be added to this bag
* @param id
* @param splitInputLine format column{separator}value, which start from index 1
* @throws ExecException
*/
protected void parseColumnValues(DataBag outputBag, String id,
String[] splitInputLine) throws ExecException {
for (int i = 1; i < splitInputLine.length; i++) {
if (splitInputLine[i] != null) {
int columnValueSplitIndex = splitInputLine[i].indexOf(this.columnValueSeparator);
if (columnValueSplitIndex != -1) {
String column = splitInputLine[i].substring(0, columnValueSplitIndex);
String value = null;
if (columnValueSplitIndex + 1 < splitInputLine[i].length()) {
value = splitInputLine[i].substring(columnValueSplitIndex + 1);
}
this.addTuple(outputBag, id, column, value);
} else {
String column = splitInputLine[i];
this.addTuple(outputBag, id, column, null);
}
}
}
}
/**
* input - contains only one field of type chararray, which will be split by '|'
* All inputs that are: null or of length 0 are ignored.
*/
@Override
public DataBag exec(Tuple input) throws IOException {
if (input == null || input.size() != 1 || input.isNull(0)) {
return null;
}
String inputLine = (String)input.get(0);
String[] splitInputLine = inputLine.split(this.rowsSeparator, -1);
if (splitInputLine.length > 1 && splitInputLine[0].length() > 0) {
String id = splitInputLine[0];
DataBag outputBag = bagFactory.newDefaultBag();
if (splitInputLine.length == 1) { // there is just an id in the line
this.addTuple(outputBag, id, null, null);
} else {
this.parseColumnValues(outputBag, id, splitInputLine);
}
return outputBag;
}
return null;
}
@Override
public Schema outputSchema(Schema input) {
try {
if (input.size() != 1) {
throw new RuntimeException("Expected input to have only one field");
}
Schema.FieldSchema inputFieldSchema = input.getField(0);
if (inputFieldSchema.type != DataType.CHARARRAY) {
throw new RuntimeException("Expected a CHARARRAY as input");
}
Schema tupleSchema = new Schema();
tupleSchema.add(new Schema.FieldSchema("id", DataType.CHARARRAY));
tupleSchema.add(new Schema.FieldSchema("column", DataType.CHARARRAY));
tupleSchema.add(new Schema.FieldSchema("value", DataType.CHARARRAY));
return new Schema(new Schema.FieldSchema(getSchemaName(this.getClass().getName().toLowerCase(), input), tupleSchema, DataType.BAG));
} catch (FrontendException exx) {
throw new RuntimeException(exx);
}
}
}
Here is how it is used in PIG:
register 'path to the jar';
define IdColumnValue myPackage.TupleToBagColumnValuePairs();
inpt = load '/pig_fun/input/single_tuple_to_multiple.txt' as (line:chararray);
result = foreach inpt generate FLATTEN(IdColumnValue($0)) as (id1, c2, v2);
dump result;
A good inspiration for writing UDFs with bags see DataFu source code by LinkedIn
You could write a UDF or use a PIG script with built-in functions.
For example:
-- data should be chararray, PigStorage('|') return bytearray which will not work for this example
inpt = load '/pig_fun/input/single_tuple_to_multiple.txt' as (line:chararray);
-- split by | and create a row so we can dereference it later
splt = foreach inpt generate FLATTEN(STRSPLIT($0, '\\|')) ;
-- first column is id, rest is converted into a bag and flatten it to make rows
id_vals = foreach splt generate $0 as id, FLATTEN(TOBAG(*)) as value;
-- there will be records with (id, id), but id should not have ':'
id_vals = foreach id_vals generate id, INDEXOF(value, ':') as p, STRSPLIT(value, ':', 2) as vals;
final = foreach (filter id_vals by p != -1) generate id, FLATTEN(vals) as (col, val);
dump final;
Test INPUT:
1|c1:11:33|c2:12
234|c1:21|c2:22
33|c1:31|c2:32
345|c1:41|c2:42
OUTPUT
(1,c1,11:33)
(1,c2,12)
(234,c1,21)
(234,c2,22)
(33,c1,31)
(33,c2,32)
(345,c1,41)
(345,c2,42)
I hope it helps.
Cheers.
You could use TransposeTupleToBag (UDF from DataFu lib) on the output of STRSPLIT to get the bag, and then FLATTEN the bag to create separate row per original column.