Examples with Data org.apache.sysml.runtime.instructions.cp.Data used on opensource projects

Example 61 with Data

use of org.apache.sysml.runtime.instructions.cp.Data in project incubator-systemml by apache.

the class ProgramConverter method createDeepCopyExecutionContext.

// //////////////////////////////
// CREATION of DEEP COPIES
// //////////////////////////////
/**
 * Creates a deep copy of the given execution context.
 * For rt_platform=Hadoop, execution context has a symbol table.
 *
 * @param ec execution context
 * @return execution context
 * @throws CloneNotSupportedException if CloneNotSupportedException occurs
 */
public static ExecutionContext createDeepCopyExecutionContext(ExecutionContext ec) throws CloneNotSupportedException {
    ExecutionContext cpec = ExecutionContextFactory.createContext(false, ec.getProgram());
    cpec.setVariables((LocalVariableMap) ec.getVariables().clone());
    // (each worker requires its own copy of the empty matrix object)
    for (String var : cpec.getVariables().keySet()) {
        Data dat = cpec.getVariables().get(var);
        if (dat instanceof MatrixObject && ((MatrixObject) dat).getUpdateType().isInPlace()) {
            MatrixObject mo = (MatrixObject) dat;
            MatrixObject moNew = new MatrixObject(mo);
            if (mo.getNnz() != 0) {
                // If output matrix is not empty (NNZ != 0), then local copy is created so that
                // update in place operation can be applied.
                MatrixBlock mbVar = mo.acquireRead();
                moNew.acquireModify(new MatrixBlock(mbVar));
                mo.release();
            } else {
                // create empty matrix block w/ dense representation (preferred for update in-place)
                // Creating a dense matrix block is valid because empty block not allocated and transfer
                // to sparse representation happens in left indexing in place operation.
                moNew.acquireModify(new MatrixBlock((int) mo.getNumRows(), (int) mo.getNumColumns(), false));
            }
            moNew.release();
            cpec.setVariable(var, moNew);
        }
    }
    return cpec;
}

Example 62 with Data

use of org.apache.sysml.runtime.instructions.cp.Data in project incubator-systemml by apache.

the class ProgramConverter method parseDataObject.

/**
 * NOTE: MRJobConfiguration cannot be used for the general case because program blocks and
 * related symbol tables can be hierarchically structured.
 *
 * @param in data object as string
 * @return array of objects
 */
public static Object[] parseDataObject(String in) {
    Object[] ret = new Object[2];
    StringTokenizer st = new StringTokenizer(in, DATA_FIELD_DELIM);
    String name = st.nextToken();
    DataType datatype = DataType.valueOf(st.nextToken());
    ValueType valuetype = ValueType.valueOf(st.nextToken());
    String valString = st.hasMoreTokens() ? st.nextToken() : "";
    Data dat = null;
    switch(datatype) {
        case SCALAR:
            {
                switch(valuetype) {
                    case INT:
                        dat = new IntObject(Long.parseLong(valString));
                        break;
                    case DOUBLE:
                        dat = new DoubleObject(Double.parseDouble(valString));
                        break;
                    case BOOLEAN:
                        dat = new BooleanObject(Boolean.parseBoolean(valString));
                        break;
                    case STRING:
                        dat = new StringObject(valString);
                        break;
                    default:
                        throw new DMLRuntimeException("Unable to parse valuetype " + valuetype);
                }
                break;
            }
        case MATRIX:
            {
                MatrixObject mo = new MatrixObject(valuetype, valString);
                long rows = Long.parseLong(st.nextToken());
                long cols = Long.parseLong(st.nextToken());
                int brows = Integer.parseInt(st.nextToken());
                int bcols = Integer.parseInt(st.nextToken());
                long nnz = Long.parseLong(st.nextToken());
                InputInfo iin = InputInfo.stringToInputInfo(st.nextToken());
                OutputInfo oin = OutputInfo.stringToOutputInfo(st.nextToken());
                PartitionFormat partFormat = PartitionFormat.valueOf(st.nextToken());
                UpdateType inplace = UpdateType.valueOf(st.nextToken());
                MatrixCharacteristics mc = new MatrixCharacteristics(rows, cols, brows, bcols, nnz);
                MetaDataFormat md = new MetaDataFormat(mc, oin, iin);
                mo.setMetaData(md);
                if (partFormat._dpf != PDataPartitionFormat.NONE)
                    mo.setPartitioned(partFormat._dpf, partFormat._N);
                mo.setUpdateType(inplace);
                dat = mo;
                break;
            }
        default:
            throw new DMLRuntimeException("Unable to parse datatype " + datatype);
    }
    ret[0] = name;
    ret[1] = dat;
    return ret;
}

Example 63 with Data

use of org.apache.sysml.runtime.instructions.cp.Data in project incubator-systemml by apache.

the class RemoteParForUtils method exportResultVariables.

/**
 * For remote Spark parfor workers. This is a simplified version compared to MR.
 *
 * @param workerID worker id
 * @param vars local variable map
 * @param resultVars list of result variables
 * @return list of result variables
 * @throws IOException if IOException occurs
 */
public static ArrayList<String> exportResultVariables(long workerID, LocalVariableMap vars, ArrayList<ResultVar> resultVars) throws IOException {
    ArrayList<String> ret = new ArrayList<>();
    // foreach result variables probe if export necessary
    for (ResultVar rvar : resultVars) {
        Data dat = vars.get(rvar._name);
        // export output variable to HDFS (see RunMRJobs)
        if (dat != null && dat.getDataType() == DataType.MATRIX) {
            MatrixObject mo = (MatrixObject) dat;
            if (mo.isDirty()) {
                // export result var (iff actually modified in parfor)
                mo.exportData();
                // pass output vars (scalars by value, matrix by ref) to result
                // (only if actually exported, hence in check for dirty, otherwise potential problems in result merge)
                ret.add(ProgramConverter.serializeDataObject(rvar._name, mo));
            }
        }
    }
    return ret;
}

Example 64 with Data

use of org.apache.sysml.runtime.instructions.cp.Data in project incubator-systemml by apache.

the class RemoteParForUtils method exportResultVariables.

/**
 * For remote MR parfor workers.
 *
 * @param workerID worker id
 * @param vars local variable map
 * @param resultVars list of result variables
 * @param rvarFnames ?
 * @param out output collectors
 * @throws IOException if IOException occurs
 */
public static void exportResultVariables(long workerID, LocalVariableMap vars, ArrayList<ResultVar> resultVars, HashMap<String, String> rvarFnames, OutputCollector<Writable, Writable> out) throws IOException {
    // create key and value for reuse
    LongWritable okey = new LongWritable(workerID);
    Text ovalue = new Text();
    // foreach result variables probe if export necessary
    for (ResultVar rvar : resultVars) {
        Data dat = vars.get(rvar._name);
        // export output variable to HDFS (see RunMRJobs)
        if (dat != null && dat.getDataType() == DataType.MATRIX) {
            MatrixObject mo = (MatrixObject) dat;
            if (mo.isDirty()) {
                if (ParForProgramBlock.ALLOW_REUSE_MR_PAR_WORKER && rvarFnames != null) {
                    String fname = rvarFnames.get(rvar._name);
                    if (fname != null)
                        mo.setFileName(fname);
                    // export result var (iff actually modified in parfor)
                    // note: this is equivalent to doing it in close (currently not required because 1 Task=1Map tasks, hence only one map invocation)
                    mo.exportData();
                    rvarFnames.put(rvar._name, mo.getFileName());
                } else {
                    // export result var (iff actually modified in parfor)
                    // note: this is equivalent to doing it in close (currently not required because 1 Task=1Map tasks, hence only one map invocation)
                    mo.exportData();
                }
                // pass output vars (scalars by value, matrix by ref) to result
                // (only if actually exported, hence in check for dirty, otherwise potential problems in result merge)
                String datStr = ProgramConverter.serializeDataObject(rvar._name, mo);
                ovalue.set(datStr);
                out.collect(okey, ovalue);
            }
        }
    }
}

Example 65 with Data

use of org.apache.sysml.runtime.instructions.cp.Data in project incubator-systemml by apache.

the class RemoteParWorkerMapper method close.

@Override
public void close() throws IOException {
    // cleanup cache and local tmp dir
    RemoteParForUtils.cleanupWorkingDirectories();
    // delete evicted matrices as well.
    if (ParForProgramBlock.ALLOW_REUSE_MR_PAR_WORKER) {
        for (RemoteParWorkerMapper pw : _sCache.values()) {
            LocalVariableMap vars = pw._ec.getVariables();
            for (String varName : vars.keySet()) {
                Data dat = vars.get(varName);
                if (dat instanceof MatrixObject)
                    ((MatrixObject) dat).setEmptyStatus();
            }
        }
    }
    // ensure caching is not disabled for CP in local mode
    CacheableData.enableCaching();
}