# Package org.apache.sysds.runtime.controlprogram.paramserv.dp

- Class Summary
  Class | Description
  --- | ---
  DataPartitionerSparkAggregator |
  DataPartitionerSparkMapper |
  DataPartitionLocalScheme |
  DataPartitionSparkScheme |
  DCLocalScheme | Disjoint_Contiguous data partitioner: for each worker, use a right indexing operation X[beg:end,] to obtain contiguous, non-overlapping partitions of rows.
  DCSparkScheme | Spark Disjoint_Contiguous data partitioner:
  DRLocalScheme | Data partitioner Disjoint_Random: for each worker, use a permutation multiply P[beg:end,] %*% X, where P is constructed for example with P=table(seq(1,nrow(X)),sample(nrow(X), nrow(X))), i.e., sampling without replacement to ensure disjointness.
  DRRLocalScheme | Disjoint_Round_Robin data partitioner: for each worker, use a permutation multiply or simpler a removeEmpty such as removeEmpty (target=X, margin=rows, select=(seq(1,nrow(X))%%k)==id)
  DRRSparkScheme | Spark Disjoint_Round_Robin data partitioner:
  DRSparkScheme | Spark data partitioner Disjoint_Random: For the current row block, find all the shifted place for each row (WorkerID => (row block ID, matrix)
  LocalDataPartitioner |
  ORLocalScheme | Data partitioner Overlap_Reshuffle: for each worker, use a new permutation multiply P %*% X, where P is constructed for example with P=table(seq(1,nrow(X),sample(nrow(X), nrow(X))))
  ORSparkScheme | Spark data partitioner Overlap_Reshuffle:
  SparkDataPartitioner |

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