这是代码:
public class databag extends EvalFunc<DataBag> {
TupleFactory mTupleFactory = TupleFactory.getInstance();
BagFactory mBagFactory = BagFactory.getInstance();
private DataBag result;
private String delimiterType = ": Src / dest :";
public DataBag exec(Tuple input) throws IOException {
try{
result = mBagFactory.newDefaultBag(); // change here
result.add(input);
getLogger().info("::::::: Entered try block ::::::::::::");
// create indexing for source and destination . ::: (Arraylist<Object[]>)
ConcurrentHashMap<Object, ArrayList<Integer>> srcIndexMap = new ConcurrentHashMap<Object, ArrayList<Integer>>();
ConcurrentHashMap<Object, ArrayList<Integer>> destIndexMap = new ConcurrentHashMap<Object, ArrayList<Integer>>();
// store the rows to Arraylist(Object[]) collection by converting .
ArrayList<Object[]> source = new ArrayList<Object[]>();
ArrayList<Object[]> destination = new ArrayList<Object[]>();
int srcCounter = 0;
int destCounter = 0;
ArrayList<Integer> Sourcearray = new ArrayList<Integer>();
ArrayList<Integer> Destinationarray = new ArrayList<Integer>();
for (Iterator<Tuple> iter = result.iterator(); iter.hasNext();) {
//some code here
}
我正在尝试使用for循环迭代数据包中的元组,但是对于每个元组,所有集合都将重新初始化,换句话说,它是从try块中为每个元组执行的。
输出:
INFO PigUDFpck.databag - ::::::: Entered try block ::::::::::::
PigUDFpck.databag - srcIndexMap={}
PigUDFpck.databag - inside main if loop skey=4
PigUDFpck.databag - destIndexMap.contains(skey)=false
PigUDFpck.databag - into else loop of main method
PigUDFpck.databag - ::::::: Entered try block ::::::::::::
PigUDFpck.databag - srcIndexMap={}
PigUDFpck.databag - inside main if loop skey=4
PigUDFpck.databag - destIndexMap.contains(skey)=false
PigUDFpck.databag - into else loop of main method
更新
pig 脚本
REGISTER /usr/local/pig/UDF/UDFBAG.jar;
sourcenew = LOAD 'hdfs://HADOOPMASTER:54310/DVTTest/Source1.txt' USING PigStorage(',') as (ID:int,Name:chararray,FirstName:chararray ,LastName:chararray,Vertical_Name:chararray ,Vertical_ID:chararray,Gender:chararray,DOB:chararray,Degree_Percentage:chararray ,Salary:chararray,StateName:chararray);
destnew = LOAD 'hdfs://HADOOPMASTER:54310/DVTTest/Destination1.txt' USING PigStorage(',') as (ID:int,Name:chararray,FirstName:chararray ,LastName:chararray,Vertical_Name:chararray ,Vertical_ID:chararray,Gender:chararray,DOB:chararray,Degree_Percentage:chararray ,Salary:chararray,StateName:chararray);
cogroupnew = COGROUP sourcenew BY ID inner, destnew BY ID inner;
diff_data = FOREACH cogroupnew GENERATE DIFF(sourcenew,destnew);
ids = FOREACH diff_data GENERATE FLATTEN($0);
id1 = DISTINCT( FOREACH ids GENERATE $0);
src = FILTER sourcenew BY ID == id1.$0;
finalsrc = FOREACH src GENERATE *, 'Source' as Source:chararray;
dest = FILTER destnew BY ID == id1.$0;
finaldest = FOREACH dest GENERATE *, 'Destination' as Destination:chararray;
final = UNION finalsrc,finaldest ;
A = FOREACH final GENERATE PigUDFpck.databag(*);
DUMP A;
和UDF的输入如下:
(4,JOHN Hansel,JOHN,Hansel,Banking ,4,M,20-01-1994,78.65,345000,ArkansasSrc1,Source)
(4,JOHN Hansel,JOHN,Hansel,Banking ,4,M,20-01-1994,78.65,345000,ArkansaSrc2,Source)
(4,JOHN Hansel,JOHN,Hansel,Banking ,4,M,20-01-1994,78.65,345000,Arkansasdest1,Destination)
(4,JOHN Hansel,JOHN,Hansel,Banking ,4,M,20-01-1994,78.65,345000,Arkanssdest2,Destination)
非常感谢帮助!!
提前致谢..!
最佳答案
请了解PIG是DAG生成器,并基于DAG生成Map Reduce Jobs。
较高级别的PIG结构(例如LOAD,FOREACH,JOIN)归结为较低级别的MR结构。
> Load => Mapper in MR
> GENRERATE => a function call in Mapper or Reduce
> JOIN => SHUFFLE (Join in Map Reduce)
> Filter => Filter function in Map or Reduce
由于databag函数的调用不是在Reducer的Mapper中执行的,而是被调用一次,而是多次。
对于每个输入ROW(取决于数据包UDF成为映射器或化简器的一部分),将执行dataBag。
请在Pig中执行EXPAIN命令,该命令会将PIG脚本转换为跟踪基础MR作业
详细了解,请遵循:
关于java - 对于Databag中的每个元组一次又一次地从try block 执行,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/42786346/