Esempio n. 1
0
  public String getCreateVarInstructions(String outputFileName, String outputLabel)
      throws LopsException {
    if (getDataType() == DataType.MATRIX || getDataType() == DataType.FRAME) {

      if (isTransient())
        throw new LopsException("getInstructions() should not be called for transient nodes.");

      OutputParameters oparams = getOutputParameters();
      String fmt = "";
      // TODO: following logic should change once we LOPs encode key-value-class information.
      if (oparams.getFormat() == Format.TEXT) fmt = "textcell";
      else if (oparams.getFormat() == Format.MM) fmt = "matrixmarket";
      else if (oparams.getFormat() == Format.CSV) fmt = "csv";
      else {
        if (oparams.getRowsInBlock() > 0 || oparams.getColsInBlock() > 0) fmt = "binaryblock";
        else fmt = "binarycell";
      }

      StringBuilder sb = new StringBuilder();
      sb.append("CP");
      sb.append(OPERAND_DELIMITOR);
      sb.append("createvar");
      sb.append(OPERAND_DELIMITOR);
      sb.append(outputLabel);
      sb.append(OPERAND_DELIMITOR);
      sb.append(outputFileName);
      sb.append(OPERAND_DELIMITOR);
      sb.append(false);
      sb.append(OPERAND_DELIMITOR); // only persistent reads come here!
      sb.append(fmt);
      sb.append(OPERAND_DELIMITOR);
      sb.append(oparams.getNumRows());
      sb.append(OPERAND_DELIMITOR);
      sb.append(oparams.getNumCols());
      sb.append(OPERAND_DELIMITOR);
      sb.append(oparams.getRowsInBlock());
      sb.append(OPERAND_DELIMITOR);
      sb.append(oparams.getColsInBlock());
      sb.append(OPERAND_DELIMITOR);
      sb.append(oparams.getNnz());

      /* Format-specific properties */
      if (oparams.getFormat() == Format.CSV) {
        sb.append(OPERAND_DELIMITOR);
        sb.append(createVarCSVHelper());
      }

      return sb.toString();
    } else {
      throw new LopsException(
          this.printErrorLocation() + "In Data Lop, Unexpected data type " + getDataType());
    }
  }
Esempio n. 2
0
  /**
   * Method to get CP instructions for reading/writing scalars and matrices from/to HDFS. This
   * method generates CP read/write instructions.
   */
  @Override
  public String getInstructions(String input1, String input2) throws LopsException {
    if (getOutputParameters().getFile_name() == null && operation == OperationTypes.READ)
      throw new LopsException(
          this.printErrorLocation()
              + "Data.getInstructions(): Exepecting a SCALAR data type, encountered "
              + getDataType());

    StringBuilder sb = new StringBuilder();
    if (this.getExecType() == ExecType.SPARK) sb.append("SPARK");
    else sb.append("CP");
    sb.append(OPERAND_DELIMITOR);
    if (operation == OperationTypes.READ) {
      sb.append("read");
      sb.append(OPERAND_DELIMITOR);
      sb.append(this.prepInputOperand(input1));
    } else if (operation == OperationTypes.WRITE) {
      sb.append("write");
      sb.append(OPERAND_DELIMITOR);
      sb.append(getInputs().get(0).prepInputOperand(input1));
    } else
      throw new LopsException(
          this.printErrorLocation() + "In Data Lop, Unknown operation: " + operation);

    sb.append(OPERAND_DELIMITOR);
    Lop fnameLop = _inputParams.get(DataExpression.IO_FILENAME);
    boolean literal = (fnameLop instanceof Data && ((Data) fnameLop).isLiteral());
    sb.append(prepOperand(input2, DataType.SCALAR, ValueType.STRING, literal));

    // attach outputInfo in case of matrices
    OutputParameters oparams = getOutputParameters();
    if (operation == OperationTypes.WRITE) {
      sb.append(OPERAND_DELIMITOR);
      String fmt = "";
      if (getDataType() == DataType.MATRIX) {
        if (oparams.getFormat() == Format.MM) fmt = "matrixmarket";
        else if (oparams.getFormat() == Format.TEXT) fmt = "textcell";
        else if (oparams.getFormat() == Format.CSV) fmt = "csv";
        else if (oparams.getFormat() == Format.BINARY) {
          if (oparams.getRowsInBlock() > 0 || oparams.getColsInBlock() > 0) fmt = "binaryblock";
          else fmt = "binarycell";
        } else {
          throw new LopsException("Unexpected format: " + oparams.getFormat());
        }
      } else {
        // scalars will always be written in text format
        fmt = "textcell";
      }

      sb.append(prepOperand(fmt, DataType.SCALAR, ValueType.STRING, true));

      if (oparams.getFormat() == Format.CSV) {
        Data headerLop = (Data) getNamedInputLop(DataExpression.DELIM_HAS_HEADER_ROW);
        Data delimLop = (Data) getNamedInputLop(DataExpression.DELIM_DELIMITER);
        Data sparseLop = (Data) getNamedInputLop(DataExpression.DELIM_SPARSE);

        if (headerLop.isVariable())
          throw new LopsException(
              this.printErrorLocation()
                  + "Parameter "
                  + DataExpression.DELIM_HAS_HEADER_ROW
                  + " must be a literal for a seq operation.");
        if (delimLop.isVariable())
          throw new LopsException(
              this.printErrorLocation()
                  + "Parameter "
                  + DataExpression.DELIM_DELIMITER
                  + " must be a literal for a seq operation.");
        if (sparseLop.isVariable())
          throw new LopsException(
              this.printErrorLocation()
                  + "Parameter "
                  + DataExpression.DELIM_SPARSE
                  + " must be a literal for a seq operation.");

        sb.append(OPERAND_DELIMITOR);
        sb.append(headerLop.getBooleanValue());
        sb.append(OPERAND_DELIMITOR);
        sb.append(delimLop.getStringValue());
        sb.append(OPERAND_DELIMITOR);
        sb.append(sparseLop.getBooleanValue());

        if (this.getExecType() == ExecType.SPARK) {
          boolean isInputMatrixBlock = true;
          Lop input = getInputs().get(0);
          if (input instanceof ParameterizedBuiltin
              && ((ParameterizedBuiltin) input).getOp()
                  == ParameterizedBuiltin.OperationTypes.TRANSFORM) {
            // in the case of transform input, the input will be Text strings insteadof MatrixBlocks
            // This information is used to have correct class information while accessing RDDs from
            // the symbol table
            isInputMatrixBlock = false;
          }
          sb.append(OPERAND_DELIMITOR);
          sb.append(isInputMatrixBlock);
        }
      }
    }

    return sb.toString();
  }