Package org.apache.pig.backend.hadoop.executionengine.physicalLayer.expressionOperators

Examples of org.apache.pig.backend.hadoop.executionengine.physicalLayer.expressionOperators.ConstantExpression


        mro.mapPlan.addAsLeaf(nfe1);
       
        // Now set up a POLocalRearrange which has "all" as the key and the output of the
        // foreach will be the "value" out of POLocalRearrange
        PhysicalPlan ep1 = new PhysicalPlan();
        ConstantExpression ce = new ConstantExpression(new OperatorKey(scope,nig.getNextNodeId(scope)));
        ce.setValue("all");
        ce.setResultType(DataType.CHARARRAY);
        ep1.add(ce);
       
        List<PhysicalPlan> eps = new ArrayList<PhysicalPlan>();
        eps.add(ep1);
       
        POLocalRearrange lr = new POLocalRearrange(new OperatorKey(scope,nig.getNextNodeId(scope)));
        try {
            lr.setIndex(0);
        } catch (ExecException e) {
          int errCode = 2058;
          String msg = "Unable to set index on newly created POLocalRearrange.";
            throw new PlanException(msg, errCode, PigException.BUG, e);
        }
        lr.setKeyType(DataType.CHARARRAY);
        lr.setPlans(eps);
        lr.setResultType(DataType.TUPLE);
        lr.setAlias(sort.getAlias());
        mro.mapPlan.add(lr);
        mro.mapPlan.connect(nfe1, lr);
       
        mro.setMapDone(true);
       
        POPackage pkg = new POPackage(new OperatorKey(scope,nig.getNextNodeId(scope)));
        pkg.setKeyType(DataType.CHARARRAY);
        pkg.setNumInps(1);
        boolean[] inner = {false};
        pkg.setInner(inner);
        mro.reducePlan.add(pkg);
       
        // Lets start building the plan which will have the sort
        // for the foreach
        PhysicalPlan fe2Plan = new PhysicalPlan();
        // Top level project which just projects the tuple which is coming
        // from the foreach after the package
        POProject topPrj = new POProject(new OperatorKey(scope,nig.getNextNodeId(scope)));
        topPrj.setColumn(1);
        topPrj.setResultType(DataType.TUPLE);
        topPrj.setOverloaded(true);
        fe2Plan.add(topPrj);
       
        // the projections which will form sort plans
        List<PhysicalPlan> nesSortPlanLst = new ArrayList<PhysicalPlan>();            
        if (sortKeyPlans != null) {
          for(int i=0; i<sortKeyPlans.size(); i++) {         
            nesSortPlanLst.add(sortKeyPlans.get(i));         
          }
        }else{  
          Pair<Integer,Byte>[] fields = null;
            try{
              fields = getSortCols(sort.getSortPlans());
            }catch(Exception e) {
              throw new RuntimeException(e);
            }
            // Set up the projections of the key columns
            if (fields == null) {
                PhysicalPlan ep = new PhysicalPlan();
                POProject prj = new POProject(new OperatorKey(scope,
                    nig.getNextNodeId(scope)));
                prj.setStar(true);
                prj.setOverloaded(false);
                prj.setResultType(DataType.TUPLE);
                ep.add(prj);
                nesSortPlanLst.add(ep);
            } else {
                for (int i=0; i<fields.length; i++) {
                    PhysicalPlan ep = new PhysicalPlan();
                    POProject prj = new POProject(new OperatorKey(scope,nig.getNextNodeId(scope)));
                    prj.setColumn(i);
                    prj.setOverloaded(false);
                    prj.setResultType(fields[i].second);
                    ep.add(prj);
                    nesSortPlanLst.add(ep);
                }
            }                      
        }
       
        sort.setSortPlans(nesSortPlanLst);
        sort.setResultType(DataType.BAG);
        fe2Plan.add(sort);
        fe2Plan.connect(topPrj, sort);
       
        // The plan which will have a constant representing the
        // degree of parallelism for the final order by map-reduce job
        // this will either come from a "order by parallel x" in the script
        // or will be the default number of reducers for the cluster if
        // "parallel x" is not used in the script
        PhysicalPlan rpep = new PhysicalPlan();
        ConstantExpression rpce = new ConstantExpression(new OperatorKey(scope,nig.getNextNodeId(scope)));
        rpce.setRequestedParallelism(rp);
        int val = rp;
        if(val<=0){
            HExecutionEngine eng = pigContext.getExecutionEngine();
            if(pigContext.getExecType() != ExecType.LOCAL){
                try {
                    if(val<=0)
                        val = pigContext.defaultParallel;
                    if (val<=0)
                        val = eng.getJobConf().getNumReduceTasks();
                    if (val<=0)
                        val = 1;
                } catch (Exception e) {
                    int errCode = 6015;
                    String msg = "Problem getting the default number of reduces from the Job Client.";
                    throw new MRCompilerException(msg, errCode, PigException.REMOTE_ENVIRONMENT, e);
                }
            } else {
              val = 1; // local mode, set it to 1
            }
        }
        int parallelismForSort = (rp <= 0 ? val : rp);
        rpce.setValue(parallelismForSort);
       
        rpce.setResultType(DataType.INTEGER);
        rpep.add(rpce);
       
        List<PhysicalPlan> genEps = new ArrayList<PhysicalPlan>();
        genEps.add(rpep);
        genEps.add(fe2Plan);
View Full Code Here


            currentPlan.connect(poGlobal, poPackage);
            List<Boolean> flattenLst = Arrays.asList(true, true);
           
            for (Operator op : inputs) {
                PhysicalPlan fep1 = new PhysicalPlan();
                ConstantExpression ce1 = new ConstantExpression(new OperatorKey(scope, nodeGen.getNextNodeId(scope)),cross.getRequestedParallelisam());
                ce1.setValue(inputs.size());
                ce1.setResultType(DataType.INTEGER);
                fep1.add(ce1);
               
                ConstantExpression ce2 = new ConstantExpression(new OperatorKey(scope, nodeGen.getNextNodeId(scope)),cross.getRequestedParallelisam());
                ce2.setValue(count);
                ce2.setResultType(DataType.INTEGER);
                fep1.add(ce2);
                /*Tuple ce1val = TupleFactory.getInstance().newTuple(2);
                ce1val.set(0,inputs.size());
                ce1val.set(1,count);
                ce1.setValue(ce1val);
View Full Code Here

        mro.mapPlan.addAsLeaf(nfe1);
       
        // Now set up a POLocalRearrange which has "all" as the key and the output of the
        // foreach will be the "value" out of POLocalRearrange
        PhysicalPlan ep1 = new PhysicalPlan();
        ConstantExpression ce = new ConstantExpression(new OperatorKey(scope,nig.getNextNodeId(scope)));
        ce.setValue("all");
        ce.setResultType(DataType.CHARARRAY);
        ep1.add(ce);
       
        List<PhysicalPlan> eps = new ArrayList<PhysicalPlan>();
        eps.add(ep1);
       
        POLocalRearrange lr = new POLocalRearrange(new OperatorKey(scope,nig.getNextNodeId(scope)));
        try {
            lr.setIndex(0);
        } catch (ExecException e) {
          int errCode = 2058;
          String msg = "Unable to set index on newly created POLocalRearrange.";
            throw new PlanException(msg, errCode, PigException.BUG, e);
        }
        lr.setKeyType(DataType.CHARARRAY);
        lr.setPlans(eps);
        lr.setResultType(DataType.TUPLE);
        lr.setAlias(sort.getAlias());
        mro.mapPlan.add(lr);
        mro.mapPlan.connect(nfe1, lr);
       
        mro.setMapDone(true);
       
        POPackage pkg = new POPackage(new OperatorKey(scope,nig.getNextNodeId(scope)));
        pkg.setKeyType(DataType.CHARARRAY);
        pkg.setNumInps(1);
        boolean[] inner = {false};
        pkg.setInner(inner);
        mro.reducePlan.add(pkg);
       
        // Lets start building the plan which will have the sort
        // for the foreach
        PhysicalPlan fe2Plan = new PhysicalPlan();
        // Top level project which just projects the tuple which is coming
        // from the foreach after the package
        POProject topPrj = new POProject(new OperatorKey(scope,nig.getNextNodeId(scope)));
        topPrj.setColumn(1);
        topPrj.setResultType(DataType.BAG);
        topPrj.setOverloaded(true);
        fe2Plan.add(topPrj);
       
        // the projections which will form sort plans
        List<PhysicalPlan> nesSortPlanLst = new ArrayList<PhysicalPlan>();            
        if (sortKeyPlans != null) {
          for(int i=0; i<sortKeyPlans.size(); i++) {         
            nesSortPlanLst.add(sortKeyPlans.get(i));         
          }
        }else{  
            Pair<POProject, Byte>[] sortProjs = null;
            try{
              sortProjs = getSortCols(sort.getSortPlans());
            }catch(Exception e) {
              throw new RuntimeException(e);
            }
            // Set up the projections of the key columns
            if (sortProjs == null) {
                PhysicalPlan ep = new PhysicalPlan();
                POProject prj = new POProject(new OperatorKey(scope,
                    nig.getNextNodeId(scope)));
                prj.setStar(true);
                prj.setOverloaded(false);
                prj.setResultType(DataType.TUPLE);
                ep.add(prj);
                nesSortPlanLst.add(ep);
            } else {
                for (int i=0; i<sortProjs.length; i++) {
                    POProject prj =
                        new POProject(new OperatorKey(scope,nig.getNextNodeId(scope)));
                   
                    prj.setResultType(sortProjs[i].second);
                    if(sortProjs[i].first != null && sortProjs[i].first.isProjectToEnd()){
                        if(i != sortProjs.length -1){
                            //project to end has to be the last sort column
                            throw new AssertionError("Project-range to end (x..)" +
                            " is supported in order-by only as last sort column");
                        }
                        prj.setProjectToEnd(i);
                        break;
                    }
                    else{
                        prj.setColumn(i);
                    }
                    prj.setOverloaded(false);

                    PhysicalPlan ep = new PhysicalPlan();
                    ep.add(prj);
                    nesSortPlanLst.add(ep);
                }
            }                      
        }
       
        sort.setSortPlans(nesSortPlanLst);
        sort.setResultType(DataType.BAG);
        fe2Plan.add(sort);
        fe2Plan.connect(topPrj, sort);
       
        // The plan which will have a constant representing the
        // degree of parallelism for the final order by map-reduce job
        // this will either come from a "order by parallel x" in the script
        // or will be the default number of reducers for the cluster if
        // "parallel x" is not used in the script
        PhysicalPlan rpep = new PhysicalPlan();
        ConstantExpression rpce = new ConstantExpression(new OperatorKey(scope,nig.getNextNodeId(scope)));
        rpce.setRequestedParallelism(rp);
        int val = rp;
        if(val<=0){
            HExecutionEngine eng = pigContext.getExecutionEngine();
            if(pigContext.getExecType() != ExecType.LOCAL){
                try {
                    if(val<=0)
                        val = pigContext.defaultParallel;
                    if (val<=0)
                        val = eng.getJobConf().getNumReduceTasks();
                    if (val<=0)
                        val = 1;
                } catch (Exception e) {
                    int errCode = 6015;
                    String msg = "Problem getting the default number of reduces from the Job Client.";
                    throw new MRCompilerException(msg, errCode, PigException.REMOTE_ENVIRONMENT, e);
                }
            } else {
              val = 1; // local mode, set it to 1
            }
        }
        int parallelismForSort = (rp <= 0 ? val : rp);
        rpce.setValue(parallelismForSort);
       
        rpce.setResultType(DataType.INTEGER);
        rpep.add(rpce);
       
        List<PhysicalPlan> genEps = new ArrayList<PhysicalPlan>();
        genEps.add(rpep);
        genEps.add(fe2Plan);
View Full Code Here

            // by loader as the "value" of POLocalRearrange
            // Sorting of index can possibly be achieved by using Hadoop sorting between map and reduce instead of Pig doing sort. If that is so,
            // it will simplify lot of the code below.
           
            PhysicalPlan lrPP = new PhysicalPlan();
            ConstantExpression ce = new ConstantExpression(new OperatorKey(scope,nig.getNextNodeId(scope)));
            ce.setValue("all");
            ce.setResultType(DataType.CHARARRAY);
            lrPP.add(ce);

            List<PhysicalPlan> lrInnerPlans = new ArrayList<PhysicalPlan>();
            lrInnerPlans.add(lrPP);
View Full Code Here

        mro.mapPlan.addAsLeaf(nfe1);
       
        // Now set up a POLocalRearrange which has "all" as the key and the output of the
        // foreach will be the "value" out of POLocalRearrange
        PhysicalPlan ep1 = new PhysicalPlan();
        ConstantExpression ce = new ConstantExpression(new OperatorKey(scope,nig.getNextNodeId(scope)));
        ce.setValue("all");
        ce.setResultType(DataType.CHARARRAY);
        ep1.add(ce);
       
        List<PhysicalPlan> eps = new ArrayList<PhysicalPlan>();
        eps.add(ep1);
       
        POLocalRearrange lr = new POLocalRearrange(new OperatorKey(scope,nig.getNextNodeId(scope)));
        try {
            lr.setIndex(0);
        } catch (ExecException e) {
          int errCode = 2058;
          String msg = "Unable to set index on newly created POLocalRearrange.";
            throw new PlanException(msg, errCode, PigException.BUG, e);
        }
        lr.setKeyType(DataType.CHARARRAY);
        lr.setPlans(eps);
        lr.setResultType(DataType.TUPLE);
        mro.mapPlan.add(lr);
        mro.mapPlan.connect(nfe1, lr);
       
        mro.setMapDone(true);
       
        POPackage pkg = new POPackage(new OperatorKey(scope,nig.getNextNodeId(scope)));
        pkg.setKeyType(DataType.CHARARRAY);
        pkg.setNumInps(1);
        boolean[] inner = {false};
        pkg.setInner(inner);
        mro.reducePlan.add(pkg);
       
        // Lets start building the plan which will have the sort
        // for the foreach
        PhysicalPlan fe2Plan = new PhysicalPlan();
        // Top level project which just projects the tuple which is coming
        // from the foreach after the package
        POProject topPrj = new POProject(new OperatorKey(scope,nig.getNextNodeId(scope)));
        topPrj.setColumn(1);
        topPrj.setResultType(DataType.TUPLE);
        topPrj.setOverloaded(true);
        fe2Plan.add(topPrj);
       
        // the projections which will form sort plans
        List<PhysicalPlan> nesSortPlanLst = new ArrayList<PhysicalPlan>();            
        if (sortKeyPlans != null) {
          for(int i=0; i<sortKeyPlans.size(); i++) {         
            nesSortPlanLst.add(sortKeyPlans.get(i));         
          }
        }else{  
          Pair<Integer,Byte>[] fields = null;
            try{
              fields = getSortCols(sort.getSortPlans());
            }catch(Exception e) {
              throw new RuntimeException(e);
            }
            // Set up the projections of the key columns
            if (fields == null) {
                PhysicalPlan ep = new PhysicalPlan();
                POProject prj = new POProject(new OperatorKey(scope,
                    nig.getNextNodeId(scope)));
                prj.setStar(true);
                prj.setOverloaded(false);
                prj.setResultType(DataType.TUPLE);
                ep.add(prj);
                nesSortPlanLst.add(ep);
            } else {
                for (int i=0; i<fields.length; i++) {
                    PhysicalPlan ep = new PhysicalPlan();
                    POProject prj = new POProject(new OperatorKey(scope,nig.getNextNodeId(scope)));
                    prj.setColumn(i);
                    prj.setOverloaded(false);
                    prj.setResultType(fields[i].second);
                    ep.add(prj);
                    nesSortPlanLst.add(ep);
                }
            }                      
        }
       
        sort.setSortPlans(nesSortPlanLst);
        sort.setResultType(DataType.BAG);
        fe2Plan.add(sort);
        fe2Plan.connect(topPrj, sort);
       
        // The plan which will have a constant representing the
        // degree of parallelism for the final order by map-reduce job
        // this will either come from a "order by parallel x" in the script
        // or will be the default number of reducers for the cluster if
        // "parallel x" is not used in the script
        PhysicalPlan rpep = new PhysicalPlan();
        ConstantExpression rpce = new ConstantExpression(new OperatorKey(scope,nig.getNextNodeId(scope)));
        rpce.setRequestedParallelism(rp);
        int val = rp;
        if(val<=0){
            ExecutionEngine eng = pigContext.getExecutionEngine();
            if(eng instanceof HExecutionEngine){
                try {
                    val = Math.round(0.9f * ((HExecutionEngine)eng).getJobClient().getDefaultReduces());
                    if(val<=0)
                        val = 1;
                } catch (IOException e) {
                    int errCode = 6015;
                    String msg = "Problem getting the default number of reduces from the Job Client.";
                    throw new MRCompilerException(msg, errCode, PigException.REMOTE_ENVIRONMENT, e);
                }
            } else {
              val = 1; // local mode, set it to 1
            }
        }
        int parallelismForSort = (rp <= 0 ? val : rp);
        rpce.setValue(parallelismForSort);
       
        rpce.setResultType(DataType.INTEGER);
        rpep.add(rpce);
       
        List<PhysicalPlan> genEps = new ArrayList<PhysicalPlan>();
        genEps.add(rpep);
        genEps.add(fe2Plan);
View Full Code Here

                int errCode = 2071;
                String msg = "Problem with setting up local rearrange's plans.";
                throw new ExecException(msg, errCode, PigException.BUG, pe);
            }
            LRs[i]= lr;
            ConstantExpression ce = new ConstantExpression(genKey(old));
            ce.setResultType((i==fragment)?DataType.TUPLE:DataType.BAG);
            constExps[i] = ce;
            PhysicalPlan pp = new PhysicalPlan();
            pp.add(ce);
            fePlans.add(pp);
            flatList.add(true);
View Full Code Here

                // by loader as the "value" of POLocalRearrange
                // Sorting of index can possibly be achieved by using Hadoop sorting between map and reduce instead of Pig doing sort. If that is so,
                // it will simplify lot of the code below.
               
                PhysicalPlan lrPP = new PhysicalPlan();
                ConstantExpression ce = new ConstantExpression(new OperatorKey(scope,nig.getNextNodeId(scope)));
                ce.setValue("all");
                ce.setResultType(DataType.CHARARRAY);
                lrPP.add(ce);
   
                List<PhysicalPlan> lrInnerPlans = new ArrayList<PhysicalPlan>();
                lrInnerPlans.add(lrPP);
   
View Full Code Here

        mro.mapPlan.addAsLeaf(nfe1);
       
        // Now set up a POLocalRearrange which has "all" as the key and the output of the
        // foreach will be the "value" out of POLocalRearrange
        PhysicalPlan ep1 = new PhysicalPlan();
        ConstantExpression ce = new ConstantExpression(new OperatorKey(scope,nig.getNextNodeId(scope)));
        ce.setValue("all");
        ce.setResultType(DataType.CHARARRAY);
        ep1.add(ce);
       
        List<PhysicalPlan> eps = new ArrayList<PhysicalPlan>();
        eps.add(ep1);
       
        POLocalRearrange lr = new POLocalRearrange(new OperatorKey(scope,nig.getNextNodeId(scope)));
        try {
            lr.setIndex(0);
        } catch (ExecException e) {
          int errCode = 2058;
          String msg = "Unable to set index on newly created POLocalRearrange.";
            throw new PlanException(msg, errCode, PigException.BUG, e);
        }
        lr.setKeyType(DataType.CHARARRAY);
        lr.setPlans(eps);
        lr.setResultType(DataType.TUPLE);
        mro.mapPlan.add(lr);
        mro.mapPlan.connect(nfe1, lr);
       
        mro.setMapDone(true);
       
        POPackage pkg = new POPackage(new OperatorKey(scope,nig.getNextNodeId(scope)));
        pkg.setKeyType(DataType.CHARARRAY);
        pkg.setNumInps(1);
        boolean[] inner = {false};
        pkg.setInner(inner);
        mro.reducePlan.add(pkg);
       
        // Lets start building the plan which will have the sort
        // for the foreach
        PhysicalPlan fe2Plan = new PhysicalPlan();
        // Top level project which just projects the tuple which is coming
        // from the foreach after the package
        POProject topPrj = new POProject(new OperatorKey(scope,nig.getNextNodeId(scope)));
        topPrj.setColumn(1);
        topPrj.setResultType(DataType.TUPLE);
        topPrj.setOverloaded(true);
        fe2Plan.add(topPrj);
       
        // the projections which will form sort plans
        List<PhysicalPlan> nesSortPlanLst = new ArrayList<PhysicalPlan>();            
        if (sortKeyPlans != null) {
          for(int i=0; i<sortKeyPlans.size(); i++) {         
            nesSortPlanLst.add(sortKeyPlans.get(i));         
          }
        }else{  
          Pair<Integer,Byte>[] fields = null;
            try{
              fields = getSortCols(sort.getSortPlans());
            }catch(Exception e) {
              throw new RuntimeException(e);
            }
            // Set up the projections of the key columns
            if (fields == null) {
                PhysicalPlan ep = new PhysicalPlan();
                POProject prj = new POProject(new OperatorKey(scope,
                    nig.getNextNodeId(scope)));
                prj.setStar(true);
                prj.setOverloaded(false);
                prj.setResultType(DataType.TUPLE);
                ep.add(prj);
                nesSortPlanLst.add(ep);
            } else {
                for (int i=0; i<fields.length; i++) {
                    PhysicalPlan ep = new PhysicalPlan();
                    POProject prj = new POProject(new OperatorKey(scope,nig.getNextNodeId(scope)));
                    prj.setColumn(i);
                    prj.setOverloaded(false);
                    prj.setResultType(fields[i].second);
                    ep.add(prj);
                    nesSortPlanLst.add(ep);
                }
            }                      
        }
       
        sort.setSortPlans(nesSortPlanLst);
        sort.setResultType(DataType.BAG);
        fe2Plan.add(sort);
        fe2Plan.connect(topPrj, sort);
       
        // The plan which will have a constant representing the
        // degree of parallelism for the final order by map-reduce job
        // this will either come from a "order by parallel x" in the script
        // or will be the default number of reducers for the cluster if
        // "parallel x" is not used in the script
        PhysicalPlan rpep = new PhysicalPlan();
        ConstantExpression rpce = new ConstantExpression(new OperatorKey(scope,nig.getNextNodeId(scope)));
        rpce.setRequestedParallelism(rp);
        int val = rp;
        if(val<=0){
            ExecutionEngine eng = pigContext.getExecutionEngine();
            if(pigContext.getExecType() != ExecType.LOCAL){
                try {
                    if(val<=0)
                        val = pigContext.defaultParallel;
                    if (val<=0)
                        val = ((JobConf)((HExecutionEngine)eng).getJobClient().getConf()).getNumReduceTasks();
                    if (val<=0)
                        val = 1;
                } catch (Exception e) {
                    int errCode = 6015;
                    String msg = "Problem getting the default number of reduces from the Job Client.";
                    throw new MRCompilerException(msg, errCode, PigException.REMOTE_ENVIRONMENT, e);
                }
            } else {
              val = 1; // local mode, set it to 1
            }
        }
        int parallelismForSort = (rp <= 0 ? val : rp);
        rpce.setValue(parallelismForSort);
       
        rpce.setResultType(DataType.INTEGER);
        rpep.add(rpce);
       
        List<PhysicalPlan> genEps = new ArrayList<PhysicalPlan>();
        genEps.add(rpep);
        genEps.add(fe2Plan);
View Full Code Here

                int errCode = 2071;
                String msg = "Problem with setting up local rearrange's plans.";
                throw new ExecException(msg, errCode, PigException.BUG, pe);
            }
            LRs[i] = lr;
            ConstantExpression ce = new ConstantExpression(genKey(old));
            ce.setResultType((i == fragment) ? DataType.TUPLE : DataType.BAG);
            constExps[i] = ce;
            PhysicalPlan pp = new PhysicalPlan();
            pp.add(ce);
            fePlans.add(pp);
            flatList.add(true);
View Full Code Here

                currentPlan.connect(poGlobal, poPackage);
                List<Boolean> flattenLst = Arrays.asList(true, true);

                for (Operator op : inputs) {
                    PhysicalPlan fep1 = new PhysicalPlan();
                    ConstantExpression ce1 = new ConstantExpression(new OperatorKey(scope, nodeGen.getNextNodeId(scope)),cross.getRequestedParallelism());
                    ce1.setValue(inputs.size());
                    ce1.setResultType(DataType.INTEGER);
                    fep1.add(ce1);

                    ConstantExpression ce2 = new ConstantExpression(new OperatorKey(scope, nodeGen.getNextNodeId(scope)),cross.getRequestedParallelism());
                    ce2.setValue(count);
                    ce2.setResultType(DataType.INTEGER);
                    fep1.add(ce2);
                    /*Tuple ce1val = TupleFactory.getInstance().newTuple(2);
                    ce1val.set(0,inputs.size());
                    ce1val.set(1,count);
                    ce1.setValue(ce1val);
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