# All Classes

- All Classes Interface Summary Class Summary Enum Summary Exception Summary
  Class | Description
  --- | ---
  ABitmap |
  AColGroup | Abstract Class that is the lowest class type for the Compression framework.
  AColGroup.CompressionType | Public super types of compression ColGroups supported
  AColGroupCompressed | Base class for column groups encoded Encoded in a compressed manner.
  AColGroupOffset | Base class for column groups encoded with various types of bitmap encoding.
  AColGroupValue | Base class for column groups encoded with value dictionary.
  AColumnCoCoder |
  ACostEstimate | A cost estimator interface.
  ADictionary | This dictionary class aims to encapsulate the storage and operations over unique tuple values of a column group.
  AFederatedPlanner |
  AggBinaryOp |
  AggBinaryOp.MMultMethod |
  AggBinaryOp.SparkAggType |
  AggregateBinaryCPInstruction |
  AggregateBinaryFEDInstruction |
  AggregateBinaryGPUInstruction |
  AggregateBinaryOperator |
  AggregateDropCorrectionFunction |
  AggregateOperator |
  AggregateTernaryCPInstruction |
  AggregateTernaryFEDInstruction |
  AggregateTernaryOperator |
  AggregateTernarySPInstruction |
  AggregateUnaryCPInstruction |
  AggregateUnaryCPInstruction.AUType |
  AggregateUnaryFEDInstruction |
  AggregateUnaryGPUInstruction | Implements aggregate unary instructions for CUDA
  AggregateUnaryOperator |
  AggregateUnarySketchSPInstruction |
  AggregateUnarySPInstruction |
  AggregateUnarySPInstruction.RDDUAggFunction2 | Similar to RDDUAggFunction but single output block.
  AggregateUnarySPInstruction.RDDUTensorAggFunction2 | Similar to RDDUAggFunction but single output block.
  AggUnaryOp |
  AInsertionSorter | This abstract class is for sorting the IntArrayList entries efficiently for SDC Column Groups construction.
  AIterator | Iterator interface, that returns a iterator of the indexes while also maintaining a data index.
  AMapToData | This Class's job is to link into the dictionary entries for column groups.
  AMorphingMMColGroup | Abstract class for column group types that do not perform matrix Multiplication, and decompression for performance reasons but instead transforms into another type of column group type to perform that operation.
  And |
  AOffset | Offset list encoder interface.
  AOffsetIterator | Iterator interface that only iterate through offsets without considering data index.
  Append |
  AppendCPInstruction |
  AppendCPInstruction.AppendType |
  AppendFEDInstruction |
  AppendG | TODO Additional compiler enhancements: 1) Partial Shuffle Elimination - Any full or aligned blocks could be directly output from the mappers to the result index.
  AppendGAlignedSP |
  AppendGAlignedSPInstruction |
  AppendGAlignedSPInstruction.ShiftColumnIndex |
  AppendGSPInstruction |
  AppendGSPInstruction.MergeWithShiftedBlocks |
  AppendGSPInstruction.ShiftMatrix |
  AppendM |
  AppendM.CacheType |
  AppendMSPInstruction |
  AppendPropagator |
  AppendR |
  AppendRSPInstruction |
  APreAgg | Abstract class for all the column groups that use preAggregation for Left matrix multiplications.
  ArithmeticBinaryGPUInstruction |
  ASDCZero |
  AssignmentStatement |
  AutoDiff |
  AWTreeNode | A workload tree is a compact representation of the operations on a matrix and derived intermediates, including the basic control structure and inlined functions as well as links to categories.
  AWTreeNode.WTNodeType |
  BalanceToAvgFederatedScheme | Balance to Avg Federated scheme When the parameter server runs in federated mode it cannot pull in the data which is already on the workers.
  BaseEntityModel |
  BasicProgramBlock |
  BasicTensorBlock |
  Binary |
  Binary |
  Binary | Lop to perform binary operation.
  BinaryBlockInputFormat | Custom binary block input format to return the custom record reader.
  BinaryBlockRecordReader | Custom record reader for binary block.
  BinaryBlockSerialization | This custom serialization class can be used via job.set(MRConfigurationNames.IO_SERIALIZATIONS, "org.apache.sysds.runtime.io.BinaryBlockSerialization");
  BinaryBlockSerialization.MatrixBlockDeserializer |
  BinaryBlockSerialization.MatrixBlockSerializer |
  BinaryBlockToTextCellConverter |
  BinaryCPInstruction |
  BinaryExpression |
  BinaryFEDInstruction |
  BinaryFrameFrameCPInstruction |
  BinaryFrameFrameSPInstruction |
  BinaryFrameMatrixCPInstruction |
  BinaryFrameMatrixSPInstruction |
  BinaryM | Lop to perform binary operation.
  BinaryM.VectorType |
  BinaryMatrixBVectorSPInstruction |
  BinaryMatrixMatrixCPInstruction |
  BinaryMatrixMatrixFEDInstruction |
  BinaryMatrixMatrixSPInstruction |
  BinaryMatrixScalarCPInstruction |
  BinaryMatrixScalarFEDInstruction |
  BinaryMatrixScalarSPInstruction |
  BinaryOp |
  BinaryOp.AppendMethod |
  BinaryOp.MMBinaryMethod |
  BinaryOperator |
  BinaryScalar | Lop to perform binary scalar operations.
  BinaryScalarScalarCPInstruction |
  BinarySPInstruction |
  BinaryTensorTensorBroadcastSPInstruction |
  BinaryTensorTensorCPInstruction |
  BinaryTensorTensorSPInstruction |
  BinaryUAggChain |
  BinUaggChainSPInstruction | Instruction that performs res = X / rowsum(x)
  BinUaggChainSPInstruction.RDDBinUaggChainFunction |
  Bitmap | Uncompressed representation of one or more columns in bitmap format.
  BitmapEncoder | Static functions for extracting bitmaps from a MatrixBlock.
  BitwAnd |
  BitwOr |
  BitwShiftL |
  BitwShiftR |
  BitwXor |
  BlockPartitioner | Default partitioner used for all binary block rdd operations in order to enable sufficient local aggregation independent of the aggregation direction (row/col-wise).
  BooleanArray32 |
  BooleanExpression |
  BooleanIdentifier |
  BooleanObject |
  BroadcastCPInstruction |
  BroadcastObject<T extends CacheBlock> |
  Builtin | Class with pre-defined set of objects.
  Builtin.BuiltinCode |
  BuiltinBinaryGPUInstruction |
  BuiltinConstant | These are the builtin constants
  BuiltinFunctionExpression |
  BuiltinNaryCPInstruction | Instruction to handle a variable number of input operands.
  BuiltinNarySPInstruction |
  BuiltinNarySPInstruction.PadBlocksFunction |
  Builtins | Enum to represent all builtin functions in the default name space.
  BuiltinUnaryGPUInstruction |
  ByteBuffer | Wrapper for WriteBuffer byte array per matrix/frame in order to support matrix/frame serialization outside global lock.
  ByteBufferDataInput |
  ByteClassLoader |
  CacheableData<T extends CacheBlock> | Each object of this class is a cache envelope for some large piece of data called "cache block".
  CacheableData.CacheStatus | Defines all possible cache status types for a data blob.
  CacheBlock | Interface for all blocks handled by lazy write buffer.
  CacheBlockFactory | Factory to create instances of matrix/frame blocks given internal codes.
  CacheDataInput |
  CacheDataOutput | Custom DataOutput to serialize directly into the given byte array.
  CachedReuseVariables |
  CacheEvictionQueue |
  CacheMaintenanceService |
  CacheStatistics | This singleton provides basic caching statistics in CP.
  CacheStatistics.Stat |
  CastFEDInstruction |
  CastSPInstruction |
  CBindPropagator |
  Cell | Helper class for representing text cell and binary cell records in order to allow for buffering and buffered read/write.
  CentralMoment | Lop to perform cross product operation
  CentralMomentCPInstruction |
  CentralMomentFEDInstruction |
  CentralMomentSPInstruction |
  CheckedConstraintsLog | Class counting the checked privacy constraints and the loaded privacy constraints.
  Checkpoint | Lop for checkpoint operations.
  CheckpointSPInstruction |
  CiphertextMatrix | This class abstracts over an encrypted matrix of ciphertexts.
  CLALibAppend |
  CLALibBinaryCellOp |
  CLALibCMOps |
  CLALibCompAgg |
  CLALibDecompress | Library to decompress a list of column groups into a matrix.
  CLALibLeftMultBy |
  CLALibMatrixMult |
  CLALibMMChain |
  CLALibRexpand |
  CLALibRightMultBy |
  CLALibScalar |
  CLALibSlice |
  CLALibSquash |
  CLALibTSMM |
  CLALibUnary |
  CLALibUtils |
  CM | GENERAL NOTE: * 05/28/2014: We decided to do handle weights consistently to SPSS in an operation-specific manner, i.e., we (1) round instead of casting where required (e.g.
  CM_COV_Object |
  CM_N_COVCell |
  CMOperator |
  CMOperator.AggregateOperationTypes |
  CNode |
  CNodeBinary |
  CNodeBinary.BinType |
  CNodeCell |
  CNodeData |
  CNodeMultiAgg |
  CNodeNary |
  CNodeNary.NaryType |
  CNodeOuterProduct |
  CNodeRow |
  CNodeTernary |
  CNodeTernary.TernaryType |
  CNodeTpl |
  CNodeUnary |
  CNodeUnary.UnaryType |
  CoCodeBinPacking | Column group partitioning with bin packing heuristic.
  CoCodeGreedy |
  CoCodeHybrid | This cocode strategy starts combines the use of CoCodePriorityQue and CoCodeGreedy.
  CoCodePriorityQue | Column group partitioning by number of distinct items estimated.
  CoCoderFactory |
  CoCoderFactory.PartitionerType | The Valid coCoding techniques
  CoCodeStatic | Column group co coding with static distribution heuristic.
  CodegenStatistics |
  CodegenUtils |
  CodeTemplate |
  ColGroupConst |
  ColGroupDDC | Class to encapsulate information about a column group that is encoded with dense dictionary encoding (DDC).
  ColGroupDDCFOR | Class to encapsulate information about a column group that is encoded with dense dictionary encoding (DDC).
  ColGroupDeltaDDC | Class to encapsulate information about a column group that is first delta encoded then encoded with dense dictionary encoding (DeltaDDC).
  ColGroupEmpty |
  ColGroupFactory | Factory class for constructing ColGroups.
  ColGroupIO | This has the IO responsibility of ColGroups, such that it enables to read and write ColGroups to and from a DataInput and DataOutput
  ColGroupOLE | Class to encapsulate information about a column group that is encoded with simple lists of offsets for each set of distinct values.
  ColGroupRLE | A group of columns compressed with a single run-length encoded bitmap.
  ColGroupSDC | Column group that sparsely encodes the dictionary values.
  ColGroupSDCFOR | ColGroup for Patched Frame Of Reference.
  ColGroupSDCSingle | Column group that sparsely encodes the dictionary values.
  ColGroupSDCSingleZeros | Column group that sparsely encodes the dictionary values.
  ColGroupSDCZeros | Column group that sparsely encodes the dictionary values.
  ColGroupSizes |
  ColGroupUncompressed | Column group type for columns that are stored as dense arrays of doubles.
  ColGroupUtils |
  ColIndexes |
  CollectionUtils |
  ColumnEncoder | Base class for all transform encoders providing both a row and block interface for decoding frames to matrices.
  ColumnEncoder.EncoderType |
  ColumnEncoderBin |
  ColumnEncoderBin.BinMethod |
  ColumnEncoderComposite | Simple composite encoder that applies a list of encoders in specified order.
  ColumnEncoderDummycode |
  ColumnEncoderFeatureHash | Class used for feature hashing transformation of frames.
  ColumnEncoderFeatureHash.FeatureHashSparseApplyTask |
  ColumnEncoderPassThrough |
  ColumnEncoderPassThrough.PassThroughSparseApplyTask |
  ColumnEncoderRecode |
  ColumnEncoderUDF |
  CommonThreadPool | This common thread pool provides an abstraction to obtain a shared thread pool, specifically the ForkJoinPool.commonPool, for all requests of the maximum degree of parallelism.
  CompilerConfig | Basic wrapper for all compiler configurations that are configured dynamically on a per script invocation basis.
  CompilerConfig.ConfigType |
  CompressedMatrixBlock |
  CompressedMatrixBlockFactory | Factory pattern to compress a Matrix Block into a CompressedMatrixBlock.
  CompressedSizeEstimator | Main abstract class for estimating size of compressions on columns.
  CompressedSizeEstimatorExact | Exact compressed size estimator (examines entire dataset).
  CompressedSizeEstimatorFactory |
  CompressedSizeEstimatorSample |
  CompressedSizeInfo | A helper reusable object for maintaining information about estimated compression
  CompressedSizeInfoColGroup | Information collected about a specific ColGroup's compression size.
  Compression |
  Compression.CompressConfig |
  CompressionCPInstruction |
  CompressionSettings | Compression Settings class, used as a bundle of parameters inside the Compression framework.
  CompressionSettingsBuilder | Builder pattern for Compression Settings.
  CompressionSPInstruction |
  CompressionSPInstruction.CompressionFunction |
  CompressionSPInstruction.CompressionWorkloadFunction |
  CompressionSPInstruction.SizeFunction |
  CompressionStatistics | Compression Statistics contain the main information gathered from the compression, such as sizes of the original matrix, vs the compressed representation at different stages of the compression.
  ComputationCostEstimator |
  ComputationCPInstruction |
  ComputationFEDInstruction |
  ComputationSPInstruction |
  ComputeBinaryBlockNnzFunction |
  ComputeCost | Class with methods estimating compute costs of operations.
  ConditionalPredicate |
  ConfigurableAPI | This interface defines the programmatic access to dml configuration properties (as defined in SystemDS-config.xml) to ensure API consistency across all APIs.
  ConfigurationManager | Singleton for accessing the parsed and merged system configuration.
  Connection | Interaction with SystemDS using the JMLC (Java Machine Learning Connector) API is initiated with a `Connection` object.
  Constants |
  ConstEncoding | Const encoding for cases where the entire group of columns is the same value
  ConstIdentifier |
  Converter<K1 extends org.apache.hadoop.io.Writable,​V1 extends org.apache.hadoop.io.Writable,​K2 extends org.apache.hadoop.io.Writable,​V2 extends org.apache.hadoop.io.Writable> |
  ConvertFrameBlockToIJVLines |
  ConvertMatrixBlockToIJVLines |
  ConvertStringToLongTextPair |
  CoordinatorController |
  CoordinatorService |
  CopyBinaryCellFunction |
  CopyFrameBlockFunction | General purpose copy function for binary block rdds.
  CopyFrameBlockPairFunction | General purpose copy function for binary block rdds.
  CopyMatrixBlockFunction | General purpose copy function for binary block rdds.
  CopyMatrixBlockPairFunction | General purpose copy function for binary block rdds.
  CopyTensorBlockFunction | General purpose copy function for binary block rdds.
  CopyTensorBlockPairFunction | General purpose copy function for binary block rdds.
  CopyTextInputFunction |
  CorrMatrixBlock |
  CostEstimationWrapper |
  CostEstimationWrapper.CostType |
  CostEstimator |
  CostEstimator | Base class for all potential cost estimators TODO account for shared read-only matrices when computing aggregated stats
  CostEstimator.DataFormat |
  CostEstimator.ExcludeType |
  CostEstimator.TestMeasure |
  CostEstimatorBuilder |
  CostEstimatorFactory |
  CostEstimatorFactory.CostType |
  CostEstimatorHops |
  CostEstimatorRuntime | Cost estimator for runtime programs.
  CostEstimatorStaticRuntime |
  CountDistinctOperator |
  CountDistinctOperatorTypes |
  COV | GENERAL NOTE: * 05/28/2014: We decided to do handle weights consistently to SPSS in an operation-specific manner, i.e., we (1) round instead of casting where required (e.g.
  CoVariance | Lop to compute covariance between two 1D matrices
  CovarianceCPInstruction |
  CovarianceFEDInstruction |
  CovarianceSPInstruction |
  COVOperator |
  CPInstruction |
  CPInstruction.CPType |
  CPInstructionParser |
  CPlanCSERewriter |
  CPlanMemoTable |
  CPlanMemoTable.MemoTableEntry |
  CPlanMemoTable.MemoTableEntrySet |
  CPlanOpRewriter | This cplan rewriter is meant to be the central place for any cplan enhancements before code generation.
  CpmmSPInstruction | Cpmm: cross-product matrix multiplication operation (distributed matrix multiply by join over common dimension and subsequent aggregation of partial results).
  CPOperand |
  CreateSparseBlockFunction | General purpose copy function for binary block values.
  CSRPointer | Compressed Sparse Row (CSR) format for CUDA Generalized matrix multiply is implemented for CSR format in the cuSparse library among other operations Since we assume that the matrix is stored with zero-based indexing (i.e.
  CSVReBlock | Lop to convert CSV data into SystemDS data format
  CSVReblockSPInstruction |
  Ctable | Lop to perform ternary operation.
  CTable |
  Ctable.OperationTypes |
  CtableCPInstruction |
  CtableFEDInstruction |
  CTableMap | Ctable map is an abstraction for the hashmap used for ctable's hash group-by because this structure is passed through various interfaces.
  CtableSPInstruction |
  CtableSPInstruction.MapJoinSignature1 |
  CtableSPInstruction.MapJoinSignature2 |
  CtableSPInstruction.MapJoinSignature3 |
  CudaMemoryAllocator |
  CudaSupportFunctions | DESIGN DOCUMENTATION FOR SUPPORTING LOWER PRECISION: 1.
  CumulativeAggregateSPInstruction |
  CumulativeOffsetBinary |
  CumulativeOffsetFEDInstruction |
  CumulativeOffsetSPInstruction |
  CumulativePartialAggregate |
  CustomErrorListener |
  CustomErrorListener.ParseIssueType | Parse issues can be syntax errors, validation errors, and validation warnings.
  CustomProperties |
  Dag<N extends Lop> | Class to maintain a DAG of lops and compile it into runtime instructions, incl piggybacking into jobs.
  DArrCounts |
  Data | Lop to represent data objects.
  Data |
  DataAugmentation |
  DataCharacteristics |
  DataConverter | This class provides methods to read and write matrix blocks from to HDFS using different data formats.
  DataExpression |
  DataGen | Defines a LOP that generates data.
  DataGenCPInstruction |
  DataGenOp | A DataGenOp can be rand (or matrix constructor), sequence, and sample - these operators have different parameters and use a map of parameter type to hop position.
  DataIdentifier |
  DataOp | A DataOp can be either a persistent read/write or transient read/write - writes will always have at least one input, but all types can have parameters (e.g., for csv literals of delimiter, header, etc).
  DataPartitioner | This is the base class for all data partitioner.
  DataPartitionerLocal | Partitions a given matrix into row or column partitions with a two pass-approach.
  DataPartitionerRemoteSpark | MR job class for submitting parfor remote partitioning MR jobs.
  DataPartitionerRemoteSparkMapper | NOTE: for the moment we only support binary block here TODO extend impl for binarycell and textcell Interface of Writable output in order to support both PairWritableBlock and PairWritableCell.
  DataPartitionerRemoteSparkReducer |
  DataPartitionerSparkAggregator |
  DataPartitionerSparkMapper |
  DataPartitionFederatedScheme |
  DataPartitionFederatedScheme.BalanceMetrics |
  DataPartitionFederatedScheme.Result |
  DataPartitionLocalScheme |
  DataPartitionSparkScheme |
  DataRange | A DataRange instance marks a part of a CacheableData data object.
  DatasetObject |
  DataTensorBlock |
  DblArray | Helper class used for bitmap extraction.
  DblArrayCountHashMap |
  DblArrayIntListHashMap |
  DblArrayIntListHashMap.DArrayIListEntry |
  DCLocalScheme | Disjoint_Contiguous data partitioner: for each worker, use a right indexing operation X[beg:end,] to obtain contiguous, non-overlapping partitions of rows.
  DCounts |
  DCSparkScheme | Spark Disjoint_Contiguous data partitioner:
  Decoder | Base class for all transform decoders providing both a row and block interface for decoding matrices to frames.
  DecoderComposite | Simple composite decoder that applies a list of decoders in specified order.
  DecoderDummycode | Simple atomic decoder for dummycoded columns.
  DecoderFactory |
  DecoderFactory.DecoderType |
  DecoderPassThrough | Simple atomic decoder for passing through numeric columns to the output.
  DecoderRecode | Simple atomic decoder for recoded columns.
  DeCompression |
  DeCompression.CompressConfig |
  DeCompressionCPInstruction |
  DeCompressionSPInstruction |
  DeCompressionSPInstruction.DeCompressionFunction |
  DeltaDictionary | This dictionary class is a specialization for the DeltaDDCColgroup.
  DenseBlock | This DenseBlock is an abstraction for different dense, row-major matrix formats.
  DenseBlock.Type |
  DenseBlockBool |
  DenseBlockDRB |
  DenseBlockFactory |
  DenseBlockFP32 |
  DenseBlockFP64 |
  DenseBlockInt32 |
  DenseBlockInt64 |
  DenseBlockLBool |
  DenseBlockLDRB | Dense Large Row Blocks have multiple 1D arrays (blocks), which contain complete rows.
  DenseBlockLFP32 |
  DenseBlockLFP64 |
  DenseBlockLInt32 |
  DenseBlockLInt64 |
  DenseBlockLString |
  DenseBlockString |
  DenseEncoding |
  DependencyTask<E> |
  DependencyThreadPool |
  DependencyWrapperTask<E> |
  DerbyRepository |
  DiagIndex |
  Dictionary | This dictionary class aims to encapsulate the storage and operations over unique floating point values of a column group.
  DictionaryFactory |
  DictionaryFactory.Type |
  DictLibMatrixMult | Utility interface for dictionary matrix multiplication
  DistinctCostEstimator | A Cost based estimator that based the compression and co-coding cost on the number of distinct elements in the column groups.
  Divide |
  DmlBaseListener | This class provides an empty implementation of `DmlListener`, which can be extended to create a listener which only needs to handle a subset of the available methods.
  DMLCompressionException |
  DMLCompressionStatistics |
  DMLConfig |
  DMLException | Exception occurring in the DML framework.
  DmlLexer |
  DmlListener | This interface defines a complete listener for a parse tree produced by `DmlParser`.
  DMLOptions | Set of DMLOptions that can be set through the command line and `MLContext` The values have been initialized with the default values Despite there being a DML and PyDML, this class is named DMLOptions to keep it consistent with `DMLOptions` and `DMLOptions`
  DmlParser |
  DmlParser.AccumulatorAssignmentStatementContext |
  DmlParser.AddSubExpressionContext |
  DmlParser.AssignmentStatementContext |
  DmlParser.AtomicExpressionContext |
  DmlParser.BooleanAndExpressionContext |
  DmlParser.BooleanNotExpressionContext |
  DmlParser.BooleanOrExpressionContext |
  DmlParser.BuiltinFunctionExpressionContext |
  DmlParser.CommandlineParamExpressionContext |
  DmlParser.CommandlinePositionExpressionContext |
  DmlParser.ConstDoubleIdExpressionContext |
  DmlParser.ConstFalseExpressionContext |
  DmlParser.ConstIntIdExpressionContext |
  DmlParser.ConstStringIdExpressionContext |
  DmlParser.ConstTrueExpressionContext |
  DmlParser.DataIdentifierContext |
  DmlParser.DataIdExpressionContext |
  DmlParser.DataTypeContext |
  DmlParser.ExpressionContext |
  DmlParser.ExternalFunctionDefExpressionContext |
  DmlParser.ForStatementContext |
  DmlParser.FunctionCallAssignmentStatementContext |
  DmlParser.FunctionCallMultiAssignmentStatementContext |
  DmlParser.FunctionStatementContext |
  DmlParser.IfdefAssignmentStatementContext |
  DmlParser.IfStatementContext |
  DmlParser.ImportStatementContext |
  DmlParser.IndexedExpressionContext |
  DmlParser.InternalFunctionDefExpressionContext |
  DmlParser.IterablePredicateColonExpressionContext |
  DmlParser.IterablePredicateContext |
  DmlParser.IterablePredicateSeqExpressionContext |
  DmlParser.MatrixDataTypeCheckContext |
  DmlParser.MatrixMulExpressionContext |
  DmlParser.Ml_typeContext |
  DmlParser.ModIntDivExpressionContext |
  DmlParser.MultDivExpressionContext |
  DmlParser.MultiIdExpressionContext |
  DmlParser.ParameterizedExpressionContext |
  DmlParser.ParForStatementContext |
  DmlParser.PathStatementContext |
  DmlParser.PowerExpressionContext |
  DmlParser.ProgramrootContext |
  DmlParser.RelationalExpressionContext |
  DmlParser.SimpleDataIdentifierExpressionContext |
  DmlParser.StatementContext |
  DmlParser.StrictParameterizedExpressionContext |
  DmlParser.StrictParameterizedKeyValueStringContext |
  DmlParser.TypedArgAssignContext |
  DmlParser.TypedArgNoAssignContext |
  DmlParser.UnaryExpressionContext |
  DmlParser.ValueTypeContext |
  DmlParser.WhileStatementContext |
  DMLParserWrapper | This is the main entry point for the Antlr4 parser.
  DmlPreprocessor | Minimal pre-processing of user function definitions which take precedence over built-in functions in cases where names conflict.
  DMLPrivacyException | This exception should be thrown to flag DML runtime errors related to the violation of privacy constraints.
  DMLProgram |
  DMLRuntimeException | This exception should be thrown to flag runtime errors -- DML equivalent to java.lang.RuntimeException.
  DMLScript |
  DMLScriptException | This exception should be thrown to flag DML Script errors.
  DmlSyntacticValidator |
  DmlSyntacticValidator.ConvertedDMLSyntax | Information about built in functions converted to a common format between PyDML and DML for the runtime.
  DMLTranslator |
  DMVUtils |
  DMVUtils.LEVEL_ENUM |
  DnnCPInstruction |
  DnnGPUInstruction |
  DnnOp |
  DnnParameters | This class is container that stores parameters required for executing following operations: conv2d, conv2d_backward_data, conv2d_backward_filter, maxpooling, maxpooling_backward
  DnnSPInstruction |
  DnnTransform |
  DnnUtils |
  DoubleCountHashMap |
  DoubleIdentifier |
  DoubleIntListHashMap | This class provides a memory-efficient replacement for `HashMap<Double,IntArrayList>` for restricted use cases.
  DoubleIntListHashMap.DIListEntry |
  DoubleObject |
  DoublePrecisionCudaSupportFunctions |
  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)
  EMAUtils |
  EmptyEncoding | Empty encoding for cases where the entire group of columns is zero
  Encoder |
  EncoderFactory |
  EncoderMVImpute |
  EncoderMVImpute.MVMethod |
  EncoderOmit |
  Encrypted | This class abstracts over an encrypted data.
  EntityEnum |
  EnvironmentHelper | This class is useful in setting environment variable for loading MKL library (done by Native Helper)
  Equals |
  EstimationFactors | Compressed Size Estimation factors.
  EstimationUtils |
  EstimatorBasicAvg | Basic average case estimator for matrix sparsity: sp = 1 - Math.pow(1-sp1*sp2, k)
  EstimatorBasicWorst | Basic average case estimator for matrix sparsity: sp = Math.min(1, sp1 * k) * Math.min(1, sp2 * k).
  EstimatorBitsetMM | This estimator implements a naive but rather common approach of boolean matrix multiplies which allows to infer the exact non-zero structure and thus is also useful for sparse result preallocation.
  EstimatorBitsetMM.BitsetMatrix |
  EstimatorBitsetMM.BitsetMatrix1 | This class represents a boolean matrix and provides key operations.
  EstimatorBitsetMM.BitsetMatrix2 |
  EstimatorDensityMap | This estimator implements an approach called density maps, as introduced in David Kernert, Frank Köhler, Wolfgang Lehner: SpMacho - Optimizing Sparse Linear Algebra Expressions with Probabilistic Density Estimation.
  EstimatorDensityMap.DensityMap |
  EstimatorLayeredGraph | This estimator implements an approach based on a so-called layered graph, introduced in Edith Cohen.
  EstimatorLayeredGraph.LayeredGraph |
  EstimatorMatrixHistogram | This estimator implements a remarkably simple yet effective approach for incorporating structural properties into sparsity estimation.
  EstimatorMatrixHistogram.MatrixHistogram |
  EstimatorSample | This estimator implements an approach based on row/column sampling Yongyang Yu, MingJie Tang, Walid G.
  EstimatorSampleRa | This estimator implements an approach based on row/column sampling Rasmus Resen Amossen, Andrea Campagna, Rasmus Pagh: Better Size Estimation for Sparse Matrix Products.
  EvalNaryCPInstruction | Eval built-in function instruction Note: it supports only single matrix[double] output
  ExecutionConfig | Java Wrapper to specify CUDA execution configuration for launching custom kernels
  ExecutionContext |
  ExecutionContextFactory |
  ExecutionContextMap |
  Explain |
  Explain.ExplainCounts |
  Explain.ExplainType |
  Expression |
  Expression.BinaryOp | Binary operators.
  Expression.BooleanOp | Boolean operators.
  Expression.DataOp | Data operators.
  Expression.FunctCallOp | Function call operators.
  Expression.RelationalOp | Relational operators.
  ExpressionInfo | This class exists solely to prevent compiler warnings.
  ExpressionList |
  ExtractBlockForBinaryReblock |
  ExtractGroup |
  ExtractGroup.ExtractGroupBroadcast |
  ExtractGroup.ExtractGroupJoin |
  ExtractGroupNWeights |
  FastBufferedDataInputStream |
  FastBufferedDataOutputStream | This buffered output stream is essentially a merged version of BufferedOutputStream and DataOutputStream, wrt SystemDS requirements.
  FastStringTokenizer |
  FastStringTokenizer | This string tokenizer is essentially a simplified StringTokenizer.
  Federated |
  FederatedCost | Class storing execution cost estimates for federated executions with cost estimates split into different categories such as compute, read, and transfer cost.
  FederatedCostEstimator | Cost estimator for federated executions with methods and constants for going through DML programs to estimate costs.
  FederatedData |
  FederatedData.FederatedRequestEncoder |
  FederatedDataPartitioner |
  FederatedLocalData |
  FederatedLookupTable | Lookup table mapping from a FedUniqueCoordID (funCID) to an ExecutionContextMap (ECM) so that every coordinator can address federated variables with its own local sequential variable IDs.
  FederatedMonitoringServer |
  FederatedMonitoringServerHandler |
  FederatedPlannerCostbased |
  FederatedPlannerFedAll | Baseline federated planner that compiles all hops that support federated execution on federated inputs to forced federated operations.
  FederatedPlannerFedHeuristic |
  FederatedPSControlThread |
  FederatedRange |
  FederatedReadCache |
  FederatedReadCache.ReadCacheEntry | Class representing an entry of the federated read cache.
  FederatedRequest |
  FederatedRequest.RequestType |
  FederatedResponse |
  FederatedResponse.ResponseType |
  FederatedStatistics |
  FederatedStatistics.FedStatsCollectFunction |
  FederatedStatistics.FedStatsCollection |
  FederatedUDF |
  FederatedWorker |
  FederatedWorker.FederatedResponseEncoder |
  FederatedWorkerHandler | Note: federated worker handler created for every command; and concurrent parfor threads at coordinator need separate execution contexts at the federated sites too
  FederatedWorkerHandlerException | Exception to throw when an exception occurs in FederatedWorkerHandler during handling of FederatedRequest.
  FederatedWorkloadAnalyzer |
  FederationMap |
  FederationUtils |
  FEDInstruction |
  FEDInstruction.FederatedOutput |
  FEDInstruction.FEDType |
  FEDInstructionParser |
  FEDInstructionUtils |
  FileFormatProperties |
  FileFormatPropertiesCSV |
  FileFormatPropertiesHDF5 |
  FileFormatPropertiesLIBSVM |
  FileFormatPropertiesMM |
  FileFormatPropertiesMM.MMField |
  FileFormatPropertiesMM.MMFormat |
  FileFormatPropertiesMM.MMSymmetry |
  FilterDiagMatrixBlocksFunction |
  FilterNonEmptyBlocksFunction |
  FilterNonEmptyBlocksFunction2 |
  FineGrainedPrivacy |
  FineGrainedPrivacyList | Simple implementation of retrieving fine-grained privacy constraints based on pairs in an ArrayList.
  FineGrainedPrivacyMap | Simple implementation of retrieving fine-grained privacy constraints based on iterating a LinkedHashMap.
  ForProgramBlock |
  ForStatement |
  ForStatementBlock |
  FORUtil |
  Frame | Frame encapsulates a SystemDS frame.
  FrameAppendCPInstruction |
  FrameAppendMSPInstruction |
  FrameAppendRSPInstruction |
  FrameBlock |
  FrameBlock.ColumnMetadata |
  FrameBlock.FrameMapFunction |
  FrameFormat | FrameFormat represents the different frame formats supported by the MLContext API.
  FrameGenerateReader |
  FrameGenerateReader.FrameReaderRowIrregular |
  FrameGenerateReader.FrameReaderRowRegularColIrregular |
  FrameGenerateReader.FrameReaderRowRegularColRegular |
  FrameIndexingCPInstruction |
  FrameIndexingSPInstruction | This class implements the frame indexing functionality inside Spark.
  FrameMetadata | Frame metadata, such as the number of rows, the number of columns, the number of non-zero values, the number of rows per block, and the number of columns per block in the frame.
  FrameObject |
  FrameRDDAggregateUtils |
  FrameRDDConverterUtils |
  FrameRDDConverterUtils.LongFrameToLongWritableFrameFunction |
  FrameRDDConverterUtils.LongWritableFrameToLongFrameFunction |
  FrameRDDConverterUtils.LongWritableTextToLongTextFunction |
  FrameRDDConverterUtils.LongWritableToSerFunction |
  FrameReader | Base class for all format-specific frame readers.
  FrameReaderBinaryBlock | Single-threaded frame binary block reader.
  FrameReaderBinaryBlockParallel | Multi-threaded frame binary block reader.
  FrameReaderFactory |
  FrameReaderJSONL |
  FrameReaderJSONLParallel |
  FrameReaderProto |
  FrameReaderTextCell | Single-threaded frame textcell reader.
  FrameReaderTextCellParallel | Multi-threaded frame textcell reader.
  FrameReaderTextCSV | Single-threaded frame text csv reader.
  FrameReaderTextCSVParallel | Multi-threaded frame text csv reader.
  FrameReblockBuffer |
  FrameSchema | The frame schema, stored as a list of `ValueType` values.
  FrameWriter | Base class for all format-specific frame writers.
  FrameWriterBinaryBlock | Single-threaded frame binary block writer.
  FrameWriterBinaryBlockParallel | Multi-threaded frame binary block writer.
  FrameWriterFactory |
  FrameWriterJSONL |
  FrameWriterJSONLParallel |
  FrameWriterProto |
  FrameWriterTextCell | Single-threaded frame text cell writer.
  FrameWriterTextCellParallel | Multi-threaded frame text cell writer.
  FrameWriterTextCSV | Single-threaded frame text csv writer.
  FrameWriterTextCSVParallel | Single-threaded frame text csv writer.
  FTypes |
  FTypes.AlignType |
  FTypes.FederatedPlanner |
  FTypes.FPartitioning |
  FTypes.FReplication |
  FTypes.FType |
  FunctionCallCP |
  FunctionCallCPInstruction |
  FunctionCallGraph |
  FunctionCallIdentifier |
  FunctionCallSizeInfo | Auxiliary data structure to hold function call summaries in terms of information about number of function calls, consistent dimensions, consistent sparsity, and dimension-preserving functions.
  FunctionDictionary<T extends Types.FunctionBlock> | Dictionary of all functions of a namespace, represented as a simple key-value map of function names and function statement blocks.
  FunctionObject |
  FunctionOp | This FunctionOp represents the call to a DML-bodied or external function.
  FunctionOp.FunctionType |
  FunctionProgramBlock |
  FunctionStatement |
  FunctionStatementBlock |
  GenerateReader |
  GenerateReader.GenerateReaderFrame |
  GenerateReader.GenerateReaderMatrix |
  GetMIMBFromRow |
  GPUContext | Represents a context per GPU accessible through the same JVM.
  GPUContextPool |
  GPUInstruction |
  GPUInstruction.GPUINSTRUCTION_TYPE |
  GPUInstructionParser |
  GPULazyCudaFreeMemoryManager |
  GPUMatrixMemoryManager |
  GPUMemoryAllocator |
  GPUMemoryEviction |
  GPUMemoryManager | - All cudaFree and cudaMalloc in SystemDS should go through this class to avoid OOM or incorrect results.
  GPUMemoryManager.EvictionPolicyBasedComparator | Class that governs the eviction policy
  GPUObject | Handle to a matrix block on the GPU
  GPUStatistics | Measures performance numbers when GPU mode is enabled Printed as part of `Statistics`.
  GreaterThan |
  GreaterThanEquals |
  GroupedAggregate | Lop to perform grouped aggregates
  GroupedAggregateM | Lop to perform mr map-side grouped aggregates (restriction: sum, w/o weights, ngroups), groups broadcasted
  GroupedAggregateM.CacheType |
  H5 |
  H5BTree |
  H5BufferBuilder |
  H5Constants |
  H5ContiguousDataset |
  H5DataLayoutMessage |
  H5DataSpaceMessage |
  H5DataTypeMessage |
  H5DoubleDataType |
  H5FillValueMessage |
  H5GroupSymbolTableNode |
  H5LocalHeap |
  H5Message |
  H5NilMessage |
  H5ObjectHeader |
  H5ObjectModificationTimeMessage |
  H5RootObject |
  H5RuntimeException |
  H5Superblock |
  H5SymbolTableEntry |
  H5SymbolTableMessage |
  Hash | A class containing different hashing functions.
  Hash.HashType | Available Hashing techniques
  HassAndStokes |
  HDFSTool |
  HEParamServer | This class implements Homomorphic Encryption (HE) for LocalParamServer.
  Hop |
  HopDagValidator | This class allows to check hop dags for validity, e.g., parent-child linking.
  HopRel | HopRel provides a representation of the relation between a hop, the cost of setting a given FederatedOutput value, and the input dependency with the given FederatedOutput value.
  HopRewriteRule | Base class for all hop rewrites in order to enable generic application of all rules.
  HopRewriteUtils |
  HopsException | Exception occurring in the HOP level.
  HybridCostEstimator |
  IController |
  Identifier |
  IDHandler | Functionalities for extracting numeric IDs from Hadoop taskIDs and other things related to modification of IDs.
  IDSequence | ID sequence for generating unique long identifiers with start 0 and increment 1.
  IEncode | This interface covers an intermediate encoding for the samples to improve the efficiency of the joining of sample column groups.
  IfElse |
  IfProgramBlock |
  IfStatement |
  IfStatementBlock |
  IJV | Helper class for external key/value exchange.
  ILinearize | A interface for the linearization algorithms that order the DAG nodes into a sequence of instructions to execute.
  ILinearize.DagLinearization |
  ImportStatement |
  IndexedIdentifier |
  IndexedMatrixValue |
  IndexedTensorBlock |
  IndexFunction |
  IndexingCPInstruction |
  IndexingFEDInstruction |
  IndexingOp |
  IndexingSPInstruction | This class implements the matrix indexing functionality inside Spark.
  IndexRange |
  InfrastructureAnalyzer | Central place for analyzing and obtaining static infrastructure properties such as memory and number of logical processors.
  InitFEDInstruction |
  InputOutputInfo |
  InputStreamInputFormat | Custom input format and record reader to redirect common implementation of csv read over record readers (which are required for the parallel readers) to an input stream.
  InsertionSorterFactory |
  InsertionSorterFactory.SORT_TYPE |
  InstallDependencyForIntegrationTests | This class will be used to setup dependency on Eclipse environment as well as on Jenkins server
  Instruction |
  Instruction.IType |
  InstructionParser |
  InstructionTypeCounter |
  InstructionUtils |
  IntArrayList |
  IntegerDivide |
  InterestingPoint | Interesting decision point with regard to materialization of intermediates.
  InterestingPoint.DecisionType |
  InterProceduralAnalysis | This Inter Procedural Analysis (IPA) serves two major purposes: 1) Inter-Procedure Analysis: propagate statistics from calling program into functions and back into main program.
  IntIdentifier |
  IntObject |
  IOUtilFunctions |
  IOUtilFunctions.CountRowsTask |
  IPAPass | Base class for all IPA passes.
  IPAPassApplyStaticAndDynamicHopRewrites | This rewrite applies static hop dag and statement block rewrites such as constant folding and branch removal in order to simplify statistic propagation.
  IPAPassCompressionWorkloadAnalysis | This rewrite obtains workload summaries for all hops candidates amenable for compression as a basis for workload-aware compression planning.
  IPAPassEliminateDeadCode | This rewrite eliminates unnecessary sub-DAGs that produce transient write outputs which are never consumed subsequently.
  IPAPassFlagFunctionsRecompileOnce | This rewrite marks functions with loops as recompile once in order to reduce recompilation overhead.
  IPAPassFlagNonDeterminism |
  IPAPassForwardFunctionCalls | This rewrite forwards a function call to a function with a simple function call that only consumes function parameters and literals into the original call location.
  IPAPassInlineFunctions | This rewrite inlines single statement block functions, which have fewer operations than an internal threshold.
  IPAPassPropagateReplaceLiterals | This rewrite propagates and replaces literals into functions in order to enable subsequent rewrites such as branch removal.
  IPAPassRemoveConstantBinaryOps | This rewrite identifies binary operations with constant matrices such as X * ones, where ones might be created as a vector of ones before a loop.
  IPAPassRemoveUnnecessaryCheckpoints | This rewrite identifies and removes unnecessary checkpoints, i.e., persisting of Spark RDDs into a given storage level.
  IPAPassRemoveUnusedFunctions | This rewrite identifies and removes unused functions in order to reduce compilation overhead and other overheads such as parfor worker creation, where we construct function copies.
  IPAPassReplaceEvalFunctionCalls | This rewrite applies static hop dag and statement block rewrites such as constant folding and branch removal in order to simplify statistic propagation.
  IPAPassRewriteFederatedPlan | This rewrite generates a federated execution plan by estimating and setting costs and the FederatedOutput values of all relevant hops in the DML program.
  IRepository |
  IsBlockInList |
  IsBlockInRange |
  IsFrameBlockInRange |
  IterablePredicate |
  JCudaKernels |
  JMLCUtils | Utility class containing static methods for working with JMLC.
  JSONHelper |
  KahanFunction | Runtime function type to perform the summation of values using the Kahan summation algorithm.
  KahanObject |
  KahanPlus |
  KahanPlusSq | Runtime function to perform the summation of squared values using the Kahan summation algorithm.
  KeepDataOnWorkerFederatedScheme | Keep Data on Worker Federated scheme When the parameter server runs in federated mode it cannot pull in the data which is already on the workers.
  KMVSketch | KMV synopsis(for k minimum values) Distinct-Value Estimation Kevin S.
  LanguageException | Exception occurring at the Language level.
  LanguageException.LanguageErrorCodes |
  LazyIterableIterator<T> | This class is a generic base class for lazy, single pass iterator classes in order to simplify the implementation of lazy iterators for mapPartitions use cases.
  LazyWriteBuffer |
  LazyWriteBuffer.RPolicy |
  LeftIndex |
  LeftIndex.LixCacheType |
  LeftIndexingOp |
  LeftIndexingOp.LeftIndexingMethod |
  LeftScalarOperator | Scalar operator for scalar-matrix operations with scalar on the left-hand-side.
  LegacyEncoder | Base class for all transform encoders providing both a row and block interface for decoding frames to matrices.
  LessThan |
  LessThanEquals |
  LibCommonsMath | Library for matrix operations that need invocation of Apache Commons Math library.
  LibMatrixAgg | MB: Library for matrix aggregations including ak+, uak+ for all combinations of dense and sparse representations, and corrections.
  LibMatrixBincell | Library for binary cellwise operations (incl arithmetic, relational, etc).
  LibMatrixBincell.BinaryAccessType |
  LibMatrixCountDistinct | This class contains various methods for counting the number of distinct values inside a MatrixBlock
  LibMatrixCUDA | All CUDA kernels and library calls are redirected through this class
  LibMatrixCuDNN | This class contains method that invoke CuDNN operations.
  LibMatrixCuDNNConvolutionAlgorithm | This class is a wrapper that contain necessary data structures to invoke a cudnn convolution* functions (such as cudnnConvolutionForward, etc) It implements autocloseable to simplify the LibMatrixCuDNN code and also avoids potential memory leaks.
  LibMatrixCuDNNInputRowFetcher | Performs a slice operation: out = in[(n+1):(n+1), 1:numColumns]
  LibMatrixCuDNNPoolingDescriptors | This class is a wrapper that contain necessary data structures to invoke a cudnn convolution* functions (such as cudnnConvolutionForward, etc) It implements autocloseable to simplify the LibMatrixCuDNN code and also avoids potential memory leaks.
  LibMatrixCuDNNRnnAlgorithm |
  LibMatrixCuMatMult |
  LibMatrixDatagen |
  LibMatrixDNN |
  LibMatrixDNN.PoolingType |
  LibMatrixDNNConv2d | This class contains the set of operators used for performing conv2d
  LibMatrixDNNHelper |
  LibMatrixDNNIm2Col | This class contains the different implementation of im2col operation
  LibMatrixDNNPooling | This class contains the set of operators used for performing pooling
  LibMatrixDNNRelu | This class contains the different implementation of rotate180 operation
  LibMatrixDNNRelu.ReluBackward | Performs the operation: (X gt 0) * dout
  LibMatrixDNNRotate180 | This class contains the different implementation of rotate180 operation
  LibMatrixDNNRotate180.Rotate180Worker |
  LibMatrixMult | MB: Library for matrix multiplications including MM, MV, VV for all combinations of dense, sparse, ultrasparse representations and special operations such as transpose-self matrix multiplication.
  LibMatrixNative |
  LibMatrixOuterAgg | ACS: Purpose of this library is to make some of the unary outer aggregate operator more efficient.
  LibMatrixReorg | MB: Library for selected matrix reorg operations including special cases and all combinations of dense and sparse representations.
  LibMatrixTercell | Library for ternary cellwise operations.
  LibSpoofPrimitives | This library contains all vector primitives that are used in generated source code for fused operators.
  LIBSVMReblockSPInstruction |
  LibTensorAgg |
  LibTensorBincell |
  LibTensorReorg |
  Lineage |
  LineageCache |
  LineageCacheConfig |
  LineageCacheConfig.LineageCachePolicy |
  LineageCacheConfig.ReuseCacheType |
  LineageCacheEntry |
  LineageCacheEviction |
  LineageCacheStatistics | This singleton provides basic lineage caching statistics in CP.
  LineageCodegenItem |
  LineageDebugger |
  LineageDedupBlock |
  LineageDedupUtils |
  LineageEstimator |
  LineageEstimatorStatistics |
  LineageGPUCacheEviction |
  LineageItem |
  LineageItem.LineageItemType |
  LineageItemUtils |
  LineageMap |
  LineageObject |
  LineageParser |
  LineageRecomputeUtils |
  LineageRewriteReuse |
  LineageTokenizer |
  LineageTraceable |
  ListAppendPropagator |
  ListAppendRemoveCPInstruction |
  ListIndexingCPInstruction |
  ListObject |
  ListReader |
  ListRemovePropagator |
  ListWriter |
  LiteralOp |
  LiteralReplacement |
  LiveVariableAnalysis |
  Local |
  LocalCPInstruction | A simple instruction that take whatever input it is and return it as a local matrix.
  LocalDataPartitioner |
  LocalFileUtils |
  LocalParamServer |
  LocalParWorker | Instances of this class can be used to execute tasks in parallel.
  LocalPSWorker |
  LocalTaskQueue<T> | This class provides a way of dynamic task distribution to multiple workers in local multi-threaded environments.
  LocalVariableMap | Replaces `HashMap⟨String, Data⟩` as the table of variable names and references.
  LongLongDoubleHashMap | This native long long - double hashmap is specifically designed for ctable operations which only require addvalue - extract semantics.
  LongLongDoubleHashMap.ADoubleEntry |
  LongLongDoubleHashMap.EntryType |
  Lop | Base class for all Lops.
  Lop.SimpleInstType | Lop types
  Lop.Type |
  Lop.VisitStatus |
  LopComparator<N extends Lop> | Comparator class used in sorting the LopDAG in topological order.
  LopProperties |
  LopsException |
  MapInputSignature |
  MapJoinSignature |
  MapmmChainSPInstruction |
  MapmmSPInstruction |
  MapMult |
  MapMult.CacheType |
  MapMultChain |
  MapMultChain.ChainType |
  MapperService |
  MapToBit |
  MapToByte |
  MapToChar |
  MapToCharPByte |
  MapToFactory |
  MapToFactory.MAP_TYPE |
  MapToInt |
  MapToUByte |
  MapToZero |
  MarkForLineageReuse |
  MaterializeSort |
  MatMultCP |
  Matrix | Matrix encapsulates a SystemDS matrix.
  MatrixAppendCPInstruction |
  MatrixAppendGPUInstruction | Implements the cbind and rbind functions for matrices
  MatrixAppendMSPInstruction |
  MatrixAppendRSPInstruction |
  MatrixBlock |
  MatrixBlock.SparsityEstimate |
  MatrixBlockDataInput | Any data input that is intended to support fast deserialization / read of entire blocks should implement this interface.
  MatrixBlockDataOutput | Any data output that is intended to support fast serialization / write of entire blocks should implement this interface.
  MatrixBlockDictionary |
  MatrixBuiltinGPUInstruction |
  MatrixBuiltinNaryCPInstruction |
  MatrixCell |
  MatrixCharacteristics |
  MatrixFormat | MatrixFormat represents the different matrix formats supported by the MLContext API.
  MatrixGenerateReader |
  MatrixGenerateReader.MatrixReaderRowIrregular |
  MatrixGenerateReader.MatrixReaderRowRegularColIrregular |
  MatrixGenerateReader.MatrixReaderRowRegularColRegular |
  MatrixIndexes | This represent the indexes to the blocks of the matrix.
  MatrixIndexingCPFileInstruction | This instruction is used if a single partition is too large to fit in memory.
  MatrixIndexingCPInstruction |
  MatrixIndexingGPUInstruction |
  MatrixIndexingSPInstruction | This class implements the matrix indexing functionality inside CP.
  MatrixLineagePair | Class to represent the relation between a MatrixObject and the respective LineageItem.
  MatrixMatrixArithmeticGPUInstruction |
  MatrixMatrixAxpyGPUInstruction |
  MatrixMatrixBinaryOpFunction |
  MatrixMatrixBuiltinGPUInstruction |
  MatrixMatrixRelationalBinaryGPUInstruction |
  MatrixMetadata | Matrix metadata, such as the number of rows, the number of columns, the number of non-zero values, the number of rows per block, and the number of columns per block in the matrix.
  MatrixMultiplicationPropagator | Used for propagating constraints in a matrix multiplication.
  MatrixMultiplicationPropagatorNaive | MatrixMultiplicationPropagator that overrides generateFineGrainedConstraints with a naive propagation of the fine-grained constraints.
  MatrixMultiplicationPropagatorPrivateFirst | MatrixMultiplicationPropagator that overrides generateFineGrainedConstraints by finding the private elements first followed by propagating PrivateAggregation in case of non-aggregating operator types.
  MatrixMultiplicationPropagatorPrivateFirstOptimized | MatrixMultiplicationPropagator that overrides generateFineGrainedConstraints by finding the private elements first while propagating PrivateAggregation in case of non-aggregating operator types.
  MatrixObject | Represents a matrix in control program.
  MatrixObject.UpdateType |
  MatrixReader | Base class for all format-specific matrix readers.
  MatrixReaderFactory |
  MatrixReshapeGPUInstruction |
  MatrixReshapeSPInstruction |
  MatrixScalarUnaryFunction |
  MatrixSketch<T> |
  MatrixValue |
  MatrixValue.CellIndex |
  MatrixVectorBinaryOpPartitionFunction |
  MatrixWriter | Base class for all format-specific matrix writers.
  MatrixWriterFactory |
  Mean |
  Memorizer |
  MemoryCostEstimator |
  MemoryEstimates | Memory Estimates is a helper class containing static classes that estimate the memory requirements of different types of objects in java.
  MemoTable | Memoization of federated execution alternatives.
  MemoTable | Memoization Table (hop id, worst-case matrix characteristics).
  MergeSort |
  Metadata | Abstract metadata class for MLContext API.
  MetaData | Class to store metadata associated with a file (e.g., a matrix) on disk.
  MetaDataAll |
  MetaDataFormat |
  MetaDataUtils |
  Minus |
  Minus1Multiply |
  MinusMultiply |
  MinusNz |
  MLContext | The MLContext API offers programmatic access to SystemDS on Spark from languages such as Scala, Java, and Python.
  MLContext.ExecutionType | The different types of execution environments supported by SystemDS.
  MLContext.ExplainLevel | The different explain levels supported by SystemDS.
  MLContextConversionUtil | Utility class containing methods to perform data conversions.
  MLContextException | Uncaught exception representing SystemDS exceptions that occur through the MLContext API.
  MLContextProxy | The purpose of this proxy is to shield systemds internals from direct access to MLContext which would try to load spark libraries and hence fail if these are not available.
  MLContextUtil | Utility class containing methods for working with the MLContext API.
  MLResults | MLResults handles the results returned from executing a Script using the MLContext API.
  MMChainCPInstruction |
  MMChainFEDInstruction |
  MMCJ | Lop to perform cross product operation
  MMCJ.MMCJType |
  MMFEDInstruction |
  MMNode | Helper class to represent matrix multiply operators in a DAG along with references to its abstract data handles.
  MMRJ | Lop to perform cross product operation
  MMTSJ | Lop to perform transpose-identity operation (t(X)%*%X or X%*%t(X)), used to represent CP and MR instruction but in case of MR there is an additional Aggregate at the reducers.
  MMTSJ.MMTSJType |
  MMTSJCPInstruction |
  MMTSJGPUInstruction |
  MMZip | Lop to perform zip matrix multiplication
  Modulus | Integer modulus, where we adhere to the defined R semantics: ("%% indicates x mod y and %/% indicates integer division.
  MultiAssignmentStatement |
  MultiColBitmap | Uncompressed representation of one or more columns in bitmap format.
  MultiColumnEncoder |
  Multiply |
  Multiply2 |
  MultiReturnBuiltinCPInstruction |
  MultiReturnParameterizedBuiltinCPInstruction |
  MultiReturnParameterizedBuiltinFEDInstruction |
  MultiReturnParameterizedBuiltinFEDInstruction.CreateFrameEncoder |
  MultiReturnParameterizedBuiltinFEDInstruction.ExecuteFrameEncoder |
  MultiReturnParameterizedBuiltinSPInstruction |
  MultiReturnParameterizedBuiltinSPInstruction.TransformEncodeBuild2Function |
  MultiReturnParameterizedBuiltinSPInstruction.TransformEncodeBuildFunction | This function pre-aggregates distinct values of recoded columns per partition (part of distributed recode map construction, used for recoding, binning and dummy coding).
  MultiReturnParameterizedBuiltinSPInstruction.TransformEncodeGroup2Function |
  MultiReturnParameterizedBuiltinSPInstruction.TransformEncodeGroupFunction | This function assigns codes to globally distinct values of recoded columns and writes the resulting column map in textcell (IJV) format to the output.
  MultiThreadedHop | Optional hop interface, to be implemented by multi-threaded hops.
  MultiThreadedOperator |
  Nary | Lop to perform an operation on a variable number of operands.
  NaryOp | The NaryOp Hop allows for a variable number of operands.
  NativeHEHelper |
  NativeHelper | This class helps in loading native library.
  NativeHelper.NativeBlasState |
  NativeStatistics |
  NetworkTrafficCounter |
  NodeEntityModel |
  NormalPRNGenerator | Class that can generate a stream of random numbers from standard normal distribution N(0,1).
  Not |
  NotEquals |
  OffsetByte |
  OffsetChar |
  OffsetColumnIndex |
  OffsetFactory |
  OffsetFactory.OFF_TYPE | The specific underlying types of offsets.
  OffsetSingle |
  OffsetTwo |
  Op |
  OperationsOnMatrixValues |
  Operator |
  OperatorType |
  OpMetadata |
  OpNormal |
  OpSided |
  OptimizationWrapper | Wrapper to ParFOR cost estimation and optimizer.
  Optimizer | Generic optimizer super class that defines the interface of all implemented optimizers.
  Optimizer.CostModelType |
  Optimizer.PlanInputType |
  OptimizerConstrained | Rule-Based ParFor Optimizer (time: O(n)): Applied rule-based rewrites: - see base class.
  OptimizerHeuristic | Heuristic ParFor Optimizer: This optimizer extends the rule-based optimizer by a time-based cost estimate for execution type decisions.
  OptimizerRuleBased | Rule-Based ParFor Optimizer (time: O(n)): Applied rule-based rewrites - 1) rewrite set data partitioner (incl.
  OptimizerUtils |
  OptimizerUtils.MemoryManager | Memory managers (static partitioned, unified)
  OptimizerUtils.OptimizationLevel | Optimization Types for Compilation O0 STATIC - Decisions for scheduling operations on CP/MR are based on predefined set of rules, which check if the dimensions are below a fixed/static threshold (OLD Method of choosing between CP and MR).
  OptNode | Internal representation of a plan alternative for program blocks and instructions in order to enable efficient and simple recursive enumeration and plan changes.
  OptNode.ExecType |
  OptNode.NodeType |
  OptNode.ParamType |
  OptNodeStatistics | TODO extend to right as well (see PerfTestTool, currently only trained with regard to left) TODO integrate mem and exec time for reuse?
  OptTree | Represents a complete plan of a top-level parfor.
  OptTreeConverter | Converter for creating an internal plan representation for a given runtime program and to modify/create the runtime program according to the optimized plan.
  OptTreePlanChecker |
  OptTreePlanMapping | Helper class for mapping nodes of the internal plan representation to statement blocks and hops / function call statements of a given DML program.
  OptTreePlanMappingAbstract |
  OptTreePlanMappingRuntime |
  Or |
  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:
  OuterVectorBinaryOpFunction |
  OutputParameters | class to maintain output parameters for a lop.
  OutputStatement |
  PageCache |
  Pair<K,​V> |
  PairWritableBlock | Custom writable for a pair of matrix indexes and matrix block as required for binaryblock in remote data partitioning.
  PairWritableCell | Custom writable for a pair of matrix indexes and matrix cell as required for binarycell in remote data partitioning.
  ParameterBuilder | Class to help setting variables in a script.
  ParameterExpression |
  ParameterizedBuiltin | Defines a LOP for functions.
  ParameterizedBuiltin | Function object for builtin function that takes a list of name=value parameters.
  ParameterizedBuiltin.ParameterizedBuiltinCode |
  ParameterizedBuiltin.ProbabilityDistributionCode |
  ParameterizedBuiltinCPInstruction |
  ParameterizedBuiltinFEDInstruction |
  ParameterizedBuiltinFEDInstruction.DecodeMatrix |
  ParameterizedBuiltinFunctionExpression |
  ParameterizedBuiltinOp | Defines the HOP for calling an internal function (with custom parameters) from a DML script.
  ParameterizedBuiltinSPInstruction |
  ParameterizedBuiltinSPInstruction.CreateMatrixCell |
  ParameterizedBuiltinSPInstruction.RDDFrameReplaceFunction |
  ParameterizedBuiltinSPInstruction.RDDMapGroupedAggFunction |
  ParameterizedBuiltinSPInstruction.RDDMapGroupedAggFunction2 | Similar to RDDMapGroupedAggFunction but single output block.
  ParameterizedBuiltinSPInstruction.RDDRemoveEmptyFunction |
  ParameterizedBuiltinSPInstruction.RDDRemoveEmptyFunctionInMem |
  ParameterizedBuiltinSPInstruction.RDDReplaceFunction |
  ParameterizedBuiltinSPInstruction.RDDRExpandFunction |
  ParameterizedBuiltinSPInstruction.RDDTokenizeFunction |
  ParameterizedBuiltinSPInstruction.RDDTransformApplyFunction |
  ParameterizedBuiltinSPInstruction.RDDTransformApplyOffsetFunction |
  ParameterizedBuiltinSPInstruction.RDDTransformDecodeExpandFunction |
  ParameterizedBuiltinSPInstruction.RDDTransformDecodeFunction |
  ParamservBuiltinCPInstruction |
  ParamServer |
  ParamServStatistics |
  ParamservUtils |
  ParForBody | Wrapper for exchanging parfor body data structures.
  ParForProgramBlock | The ParForProgramBlock has the same execution semantics as a ForProgamBlock but executes the independent iterations in parallel.
  ParForProgramBlock.PartitionFormat | Convenience class to package PDataPartitionFormat and its parameters.
  ParForProgramBlock.PDataPartitioner |
  ParForProgramBlock.PDataPartitionFormat |
  ParForProgramBlock.PExecMode |
  ParForProgramBlock.POptMode |
  ParForProgramBlock.PResultMerge |
  ParForProgramBlock.PTaskPartitioner |
  ParForStatement | This ParForStatement is essentially identical to a ForStatement, except an extended toString method for printing the 'parfor' keyword.
  ParForStatementBlock | This ParForStatementBlock is essentially identical to a ForStatementBlock, except an extended validate for checking/setting optional parfor parameters and running the loop dependency analysis.
  ParForStatementBlock.ResultVar |
  ParForStatistics |
  ParseException | This exception is thrown when parse issues are encountered.
  ParseInfo |
  ParserFactory |
  ParserWrapper | Base class for all dml parsers in order to make the various compilation chains independent of the used parser.
  PartialAggregate | Lop to perform a partial aggregation.
  PartitionedBlock<T extends CacheBlock> | This class is for partitioned matrix/frame blocks, to be used as broadcasts.
  PartitionedBroadcast<T extends CacheBlock> | This class is a wrapper around an array of broadcasts of partitioned matrix/frame blocks, which is required due to 2GB limitations of Spark's broadcast handling.
  ParWorker | Super class for master/worker pattern implementations.
  PathStatement |
  PerformGroupByAggInCombiner |
  PerformGroupByAggInReducer |
  PickByCount |
  PickByCount.OperationTypes |
  PlaintextMatrix | This class abstracts over an encrypted matrix of ciphertexts.
  PlanAnalyzer | Utility functions to extract structural information from the memo table, including connected components (aka partitions) of partial fusion plans, materialization points of partitions, and root nodes of partitions.
  PlanPartition |
  PlanSelection |
  PlanSelection.VisitMarkCost |
  PlanSelectionFuseAll | This plan selection heuristic aims for maximal fusion, which potentially leads to overlapping fused operators and thus, redundant computation but with a minimal number of materialized intermediate results.
  PlanSelectionFuseCostBased | This cost-based plan selection algorithm chooses fused operators based on the DAG structure and resulting overall costs.
  PlanSelectionFuseCostBasedV2 | This cost-based plan selection algorithm chooses fused operators based on the DAG structure and resulting overall costs.
  PlanSelectionFuseNoRedundancy | This plan selection heuristic aims for fusion without any redundant computation, which, however, potentially leads to more materialized intermediates than the fuse all heuristic.
  Plus |
  PlusMultiply |
  PMapmmSPInstruction | This pmapmm matrix multiplication instruction is still experimental not integrated in automatic operator selection yet.
  PMapMult |
  PMMJ |
  PMMJ.CacheType |
  PMMJCPInstruction |
  PmmSPInstruction |
  PoissonPRNGenerator | Class that can generate a stream of random numbers from Poisson distribution with specified mean.
  PorterStemmer | Stemmer, implementing the Porter Stemming Algorithm The Stemmer class transforms a word into its root form.
  Power |
  Power2 |
  PrefetchCPInstruction |
  PreparedScript | Representation of a prepared (precompiled) DML/PyDML script.
  PrintStatement |
  PrintStatement.PRINTTYPE | The PRINTTYPE options are: PRINT, PRINTF, and STOP.
  PrivacyConstraint | PrivacyConstraint holds all privacy constraints for data in the system at compile time and runtime.
  PrivacyConstraint.PrivacyLevel |
  PrivacyMonitor |
  PrivacyPropagator | Class with static methods merging privacy constraints of operands in expressions to generate the privacy constraints of the output.
  PrivacyUtils |
  PRNGenerator |
  Program |
  ProgramBlock |
  ProgramConverter | Program converter functionalities for (1) creating deep copies of program blocks, instructions, function program blocks, and (2) serializing and parsing of programs, program blocks, functions program blocks.
  ProgramRecompiler |
  ProgramRewriter | This program rewriter applies a variety of rule-based rewrites on all hop dags of the given program in one pass over the entire program.
  ProgramRewriteStatus |
  ProjectInfo | Obtains information that is stored in the manifest when the SystemDS jar is built.
  Propagator | Interface for all propagator instances with a single output.
  PropagatorMultiReturn | Interface for all propagator instances with multiple outputs.
  PSRpcCall |
  PSRpcFactory |
  PSRpcHandler |
  PSRpcObject |
  PSRpcResponse |
  PSRpcResponse.Type |
  PSWorker |
  PublicKey |
  Py4jConverterUtils | Utils for converting python data to java.
  PythonDMLScript |
  QDictionary | This dictionary class aims to encapsulate the storage and operations over unique floating point values of a column group.
  QuantilePickCPInstruction |
  QuantilePickFEDInstruction |
  QuantilePickFEDInstruction.CreateMatrixFromFrame |
  QuantilePickFEDInstruction.GetHistogram |
  QuantilePickFEDInstruction.GetValuesInRange |
  QuantilePickFEDInstruction.GetValuesInRanges |
  QuantilePickFEDInstruction.MinMax |
  QuantilePickSPInstruction |
  QuantileSortCPInstruction | This class supports two variants of sort operation on a 1-dimensional input matrix.
  QuantileSortFEDInstruction |
  QuantileSortSPInstruction | This class supports two variants of sort operation on a 1-dimensional input matrix.
  QuaternaryCPInstruction |
  QuaternaryFEDInstruction |
  QuaternaryOp | Note: this hop should be called AggQuaternaryOp in consistency with AggUnaryOp and AggBinaryOp; however, since there does not exist a real QuaternaryOp yet - we can leave it as is for now.
  QuaternaryOperator |
  QuaternarySPInstruction |
  QuaternaryWCeMMFEDInstruction |
  QuaternaryWDivMMFEDInstruction |
  QuaternaryWSigmoidFEDInstruction |
  QuaternaryWSLossFEDInstruction |
  QuaternaryWUMMFEDInstruction |
  RandNPair | Class that generates a pair of random numbers from standard normal distribution N(0,1).
  RandomMatrixGenerator |
  RandomMatrixGenerator.PDF | Types of Probability density functions
  RandSPInstruction |
  RawRow |
  RBindPropagator |
  RDDAggregateUtils | Collection of utility methods for aggregating binary block rdds.
  RDDConverterUtils |
  RDDConverterUtils.BinaryCellToBinaryBlockFunction |
  RDDConverterUtils.DataFrameExtractIDFunction |
  RDDConverterUtilsExt | NOTE: These are experimental converter utils.
  RDDConverterUtilsExt.AddRowID |
  RDDConverterUtilsExt.RDDConverterTypes |
  RDDObject |
  RDDSortUtils |
  RDDSortUtils.IndexComparator |
  RDDSortUtils.IndexComparator2 |
  ReachabilityGraph |
  ReachabilityGraph.SubProblem |
  ReaderBinaryBlock |
  ReaderBinaryBlockParallel |
  ReaderColumnSelection | Base class for all column selection readers.
  ReaderColumnSelectionDenseMultiBlock |
  ReaderColumnSelectionDenseMultiBlockTransposed |
  ReaderColumnSelectionDenseSingleBlock |
  ReaderColumnSelectionDenseSingleBlockTransposed |
  ReaderColumnSelectionSparse | Used to extract the values at certain indexes from each row in a sparse matrix Keeps returning all-zeros arrays until reaching the last possible index.
  ReaderColumnSelectionSparseTransposed | Used to extract the values at certain indexes from each row in a sparse matrix Keeps returning all-zeros arrays until reaching the last possible index.
  ReaderHDF5 |
  ReaderHDF5Parallel |
  ReaderMapping |
  ReaderMapping.FrameReaderMapping |
  ReaderMapping.MatrixReaderMapping |
  ReaderTextCell |
  ReaderTextCellParallel | Parallel version of ReaderTextCell.java.
  ReaderTextCellParallel.CellBuffer | Useful class for buffering unordered cells before locking target onces and appending all buffered cells.
  ReaderTextCellParallel.CountNnzTask |
  ReaderTextCellParallel.ReadTask |
  ReaderTextCSV |
  ReaderTextCSVParallel | Parallel version of ReaderTextCSV.java.
  ReaderTextLIBSVM |
  ReaderTextLIBSVMParallel |
  ReaderWriterFederated | This class serves as the reader for federated objects.
  ReadProperties |
  ReBlock | Lop to perform reblock operation
  ReblockBuffer |
  ReblockFEDInstruction |
  ReblockSPInstruction |
  ReblockTensorFunction |
  Recompiler | Dynamic recompilation of hop dags to runtime instructions, which includes the following substeps: (1) deep copy hop dag, (2) refresh matrix characteristics, (3) apply dynamic rewrites, (4) refresh memory estimates, (5) construct lops (incl operator selection), and (6) generate runtime program (incl piggybacking).
  Recompiler.ResetType |
  RecompileStatistics |
  RecompileStatus |
  RecomputeNnzFunction |
  ReduceAll |
  ReduceCol |
  ReduceDiag |
  ReduceRow |
  ReIndexOperator |
  RelationalBinaryGPUInstruction |
  RelationalExpression |
  RemoteDPParForSpark | TODO heavy hitter maintenance TODO data partitioning with binarycell
  RemoteDPParForSparkWorker |
  RemoteParForJobReturn | Wrapper for job return of ParFor REMOTE for transferring statistics and result symbol table.
  RemoteParForSpark | This class serves two purposes: (1) isolating Spark imports to enable running in environments where no Spark libraries are available, and (2) to follow the same structure as the parfor remote_mr job submission.
  RemoteParForSparkWorker |
  RemoteParForUtils | Common functionalities for parfor workers in MR jobs.
  ReorgCPInstruction |
  ReorgFEDInstruction |
  ReorgFEDInstruction.DiagMatrix |
  ReorgFEDInstruction.Rdiag |
  ReorgGPUInstruction |
  ReorgMapFunction |
  ReorgOp | Reorg (cell) operation: aij Properties: Symbol: ', rdiag, rshape, rsort 1 Operand (except sort and reshape take additional arguments) Semantic: change indices (in mapper or reducer) NOTE MB: reshape integrated here because (1) ParameterizedBuiltinOp requires name-value pairs for params and (2) most importantly semantic of reshape is exactly a reorg op.
  ReorgOperator |
  ReorgSPInstruction |
  ReplicateBlockFunction |
  ReplicateTensorFunction |
  ReplicateToMaxFederatedScheme | Replicate to Max Federated scheme When the parameter server runs in federated mode it cannot pull in the data which is already on the workers.
  ReplicateVectorFunction |
  Request |
  ReshapeCPInstruction |
  ReshapeFEDInstruction |
  Response |
  ResultMerge<T extends CacheableData<?>> |
  ResultMergeFrameLocalMemory |
  ResultMergeLocalAutomatic |
  ResultMergeLocalFile | TODO potential extension: parallel merge (create individual staging files concurrently) NOTE: file merge typically used due to memory constraints - parallel merge would increase the memory consumption again.
  ResultMergeLocalMemory | Local in-memory realization of result merge.
  ResultMergeMatrix | Due to independence of all iterations, any result has the following properties: (1) non local var, (2) matrix object, and (3) completely independent.
  ResultMergeRemoteGrouping |
  ResultMergeRemoteSorting |
  ResultMergeRemoteSpark |
  ResultMergeRemoteSparkWCompare |
  ResultMergeTaggedMatrixIndexes | This class serves as composite key for the remote result merge job (for any data format) in order to sort on both matrix indexes and tag but group all blocks according to matrix indexes only.
  ResultVariables | A ResultVariables object holds the data returned by a call to `PreparedScript`'s `executeScript` method, which executes a DML/PyDML script.
  RevIndex |
  RewriteAlgebraicSimplificationDynamic | Rule: Algebraic Simplifications.
  RewriteAlgebraicSimplificationStatic | Rule: Algebraic Simplifications.
  RewriteBlockSizeAndReblock | Rule: BlockSizeAndReblock.
  RewriteCommonSubexpressionElimination | Rule: CommonSubexpressionElimination.
  RewriteCompressedReblock | Rule: Compressed Re block if config compressed.linalg is enabled, we inject compression directions after read of matrices if number of rows is above 1000 and cols at least 1.
  RewriteConstantFolding | Rule: Constant Folding.
  RewriteElementwiseMultChainOptimization | Prerequisite: RewriteCommonSubexpressionElimination must run before this rule.
  RewriteFederatedExecution |
  RewriteFederatedExecution.PrivacyConstraintRetriever | FederatedUDF for retrieving privacy constraint of data stored in file name.
  RewriteForLoopVectorization | Rule: Simplify program structure by pulling if or else statement body out (removing the if statement block ifself) in order to allow intra-procedure analysis to propagate exact statistics.
  RewriteGPUSpecificOps |
  RewriteHoistLoopInvariantOperations | Rule: Simplify program structure by hoisting loop-invariant operations out of while, for, or parfor loops.
  RewriteIndexingVectorization | Rule: Indexing vectorization.
  RewriteInjectSparkLoopCheckpointing | Rule: Insert checkpointing operations for caching purposes.
  RewriteInjectSparkPReadCheckpointing | Rule: BlockSizeAndReblock.
  RewriteMarkLoopVariablesUpdateInPlace | Rule: Mark loop variables that are only read/updated through cp left indexing for update in-place.
  RewriteMatrixMultChainOptimization | Rule: Determine the optimal order of execution for a chain of matrix multiplications Solution: Classic Dynamic Programming Approach: Currently, the approach based only on matrix dimensions Goal: To reduce the number of computations in the run-time (map-reduce) layer
  RewriteMatrixMultChainOptimizationSparse | Rule: Determine the optimal order of execution for a chain of matrix multiplications Solution: Classic Dynamic Programming Approach: Currently, the approach based only on matrix dimensions and sparsity estimates using the MNC sketch Goal: To reduce the number of computations in the run-time (map-reduce) layer
  RewriteMergeBlockSequence | Rule: Simplify program structure by merging sequences of last-level statement blocks in order to create optimization opportunities.
  RewriteRemoveDanglingParentReferences | This rewrite is a general-purpose cleanup pass that removes any dangling parent references in one pass through the hop DAG.
  RewriteRemoveEmptyBasicBlocks | Rule: Simplify program structure by removing empty last-level blocks, which may originate from the original program or due to a sequence of rewrites (e.g., checkpoint injection and subsequent IPA).
  RewriteRemoveForLoopEmptySequence | Rule: Simplify program structure by removing (par)for statements iterating over an empty sequence, i.e., (par)for-loops without a single iteration.
  RewriteRemovePersistentReadWrite | This rewrite is a custom rewrite for JMLC in order to replace all persistent reads and writes with transient reads and writes from the symbol table.
  RewriteRemoveReadAfterWrite | Rule: RemoveReadAfterWrite.
  RewriteRemoveUnnecessaryBranches | Rule: Simplify program structure by pulling if or else statement body out (removing the if statement block ifself) in order to allow intra-procedure analysis to propagate exact statistics.
  RewriteRemoveUnnecessaryCasts | Rule: RemoveUnnecessaryCasts.
  RewriteSplitDagDataDependentOperators | Rule: Split Hop DAG after specific data-dependent operators.
  RewriteSplitDagUnknownCSVRead | Rule: Split Hop DAG after CSV reads with unknown size.
  RewriteTransientWriteParentHandling | Rule: Eliminate for Transient Write DataHops to have no parents Solution: Move parent edges of Transient Write Hop to parent of its child Reason: Transient Write not being a root messes up analysis for Lop's to Instruction translation (according to Amol)
  RightIndex |
  RightScalarOperator | Scalar operator for scalar-matrix operations with scalar on the right-hand-side.
  RmmSPInstruction |
  RowMatrixBlock |
  SampleEstimatorFactory |
  SampleEstimatorFactory.EstimationType |
  SampleProperties |
  ScalarAppendCPInstruction |
  ScalarBuiltinNaryCPInstruction | The ScalarBuiltinMultipleCPInstruction class is responsible for printf-style Java-based string formatting.
  ScalarMatrixArithmeticGPUInstruction |
  ScalarMatrixBuiltinGPUInstruction |
  ScalarMatrixRelationalBinaryGPUInstruction |
  ScalarObject |
  ScalarObjectFactory |
  ScalarOperator | Base class for all scalar operators.
  Script | A Script object encapsulates a DML or PYDML script.
  ScriptExecutor | ScriptExecutor executes a DML or PYDML Script object using SystemDS.
  ScriptExecutorUtils |
  ScriptFactory | Factory for creating DML and PYDML Script objects from strings, files, URLs, and input streams.
  SEALClient |
  SEALServer |
  SerLongWritable | Wrapper for LongWritable in order to make it serializable as required for shuffle in spark instructions.
  SerText | Wrapper for Text in order to make it serializable as required for shuffle in spark instructions.
  ShadowBuffer |
  ShlosserEstimator |
  ShlosserJackknifeEstimator |
  ShuffleFederatedScheme | Shuffle Federated scheme When the parameter server runs in federated mode it cannot pull in the data which is already on the workers.
  SimpleOperator |
  SinglePrecisionCudaSupportFunctions |
  SingletonLookupHashMap | This class allows sharing of objects across the entire program.
  SmallestPriorityQueue | Deceiving name, but is used to contain the k smallest values inserted.
  SmoothedJackknifeEstimator |
  SortIndex | This index function is NOT used for actual sorting but just as a reference in ReorgOperator in order to identify sort operations.
  SortKeys |
  SortKeys.OperationTypes |
  SortUtils | Utilities for sorting, primarily used for SparseRows.
  SparkDataPartitioner |
  SparkExecutionContext |
  SparkExecutionContext.SparkClusterConfig | Captures relevant spark cluster configuration properties, e.g., memory budgets and degree of parallelism.
  SparkParamservUtils |
  SparkPSBody | Wrapper class containing all needed for launching spark remote worker
  SparkPSProxy |
  SparkPSWorker |
  SparkStatistics |
  SparkUtils |
  SparseBlock | This SparseBlock is an abstraction for different sparse matrix formats.
  SparseBlock.Type |
  SparseBlockCOO | SparseBlock implementation that realizes a traditional 'coordinate matrix' representation, where the entire sparse block is stored as triples in three arrays: row indexes, column indexes, and values, where row indexes and colunm indexes are sorted in order to allow binary search.
  SparseBlockCSR | SparseBlock implementation that realizes a traditional 'compressed sparse row' representation, where the entire sparse block is stored as three arrays: ptr of length rlen+1 to store offsets per row, and indexes/values of length nnz to store column indexes and values of non-zero entries.
  SparseBlockFactory |
  SparseBlockMCSR | SparseBlock implementation that realizes a 'modified compressed sparse row' representation, where each compressed row is stored as a separate SparseRow object which provides flexibility for unsorted row appends without the need for global reshifting of values/indexes but it incurs additional memory overhead per row for object/array headers per row which also slows down memory-bound operations due to higher memory bandwidth requirements.
  SparseEncoding | Most common is zero encoding
  SparseRow | Base class for sparse row implementations such as sparse row vectors and sparse scalars (single value per row).
  SparseRowScalar |
  SparseRowVector |
  SparsityEstimator |
  SparsityEstimator.OpCode |
  SPInstruction |
  SPInstruction.SPType |
  SPInstructionParser |
  SpoofCellwise |
  SpoofCellwise.AggOp |
  SpoofCellwise.CellType |
  SpoofCompiler |
  SpoofCompiler.CompilerType |
  SpoofCompiler.GeneratorAPI |
  SpoofCompiler.IntegrationType |
  SpoofCompiler.PlanCachePolicy |
  SpoofCompiler.PlanSelector |
  SpoofCompiler.RegisterAlloc |
  SpoofCPInstruction |
  SpoofCUDACellwise |
  SpoofCUDAInstruction |
  SpoofCUDAInstruction.DoublePrecision |
  SpoofCUDAInstruction.SinglePrecision |
  SpoofCUDAOperator |
  SpoofCUDAOperator.PrecisionProxy |
  SpoofCUDARowwise |
  SpoofFEDInstruction |
  SpoofFused |
  SpoofFusedOp |
  SpoofFusedOp.SpoofOutputDimsType |
  SpoofMultiAggregate |
  SpoofOperator |
  SpoofOperator.SideInput |
  SpoofOperator.SideInputSparseCell |
  SpoofOperator.SideInputSparseRow |
  SpoofOuterProduct |
  SpoofOuterProduct.OutProdType |
  SpoofRowwise |
  SpoofRowwise.RowType |
  SpoofSPInstruction |
  SpoofSPInstruction.ReplicateRightFactorFunction |
  Sql |
  SqlCPInstruction |
  StagingFileUtils |
  Stat | Collection of all ParFor statistic types.
  Statement |
  Statement.FederatedPSScheme |
  Statement.PSCheckpointing |
  Statement.PSFrequency |
  Statement.PSModeType |
  Statement.PSRuntimeBalancing |
  Statement.PSScheme |
  Statement.PSUpdateType |
  StatementBlock |
  StatementBlockRewriteRule | Base class for all hop rewrites in order to enable generic application of all rules.
  StatementInfo | This class exists solely to prevent compiler warnings.
  StatisticMonitor | This singleton statistic monitor is used to consolidate all parfor runtime statistics.
  Statistics | This class captures all statistics.
  StatsEntityModel |
  StatsService |
  StringIdentifier |
  StringInitCPInstruction |
  StringObject |
  SubsampleToMinFederatedScheme | Subsample to Min Federated scheme When the parameter server runs in federated mode it cannot pull in the data which is already on the workers.
  SwapIndex |
  SystemDSLoaderUtils |
  Task | A task is a logical group of one or multiple iterations (each iteration is assigned to exactly one task).
  Task.TaskType |
  TaskPartitioner | This is the base class for all task partitioner.
  TaskPartitionerFactoring | This factoring task partitioner virtually iterates over the given FOR loop (from, to, incr), creates iterations and group them to tasks.
  TaskPartitionerFactoringCmax | Factoring with maximum constraint (e.g., if LIX matrix out-of-core and we need to bound the maximum number of iterations per map task -> memory bounds)
  TaskPartitionerFactoringCmin | Factoring with minimum constraint (e.g., if communication is expensive)
  TaskPartitionerFixedsize | This naive task partitioner virtually iterates over the given FOR loop (from, to, incr), creates iterations and group them to tasks according to the given task size.
  TaskPartitionerNaive | This static task partitioner virtually iterates over the given FOR loop (from, to, incr), creates iterations and group them to tasks according to a task size of numIterations/numWorkers.
  TaskPartitionerStatic | This static task partitioner virtually iterates over the given FOR loop (from, to, incr), creates iterations and group them to tasks according to a task size of numIterations/numWorkers.
  TemplateBase |
  TemplateBase.CloseType |
  TemplateBase.TemplateType |
  TemplateCell |
  TemplateCell.HopInputComparator | Comparator to order input hops of the cell template.
  TemplateMultiAgg |
  TemplateOuterProduct |
  TemplateRow |
  TemplateRow.HopInputComparator | Comparator to order input hops of the row aggregate template.
  TemplateUtils |
  TensorBlock | A `TensorBlock` is the most top level representation of a tensor.
  TensorCharacteristics |
  TensorIndexes | This represent the indexes to the blocks of the tensor.
  TensorObject |
  TensorReader |
  TensorReaderBinaryBlock |
  TensorReaderBinaryBlockParallel |
  TensorReaderFactory |
  TensorReaderTextCell |
  TensorReaderTextCellParallel |
  TensorTensorBinaryOpFunction |
  TensorTensorBinaryOpPartitionFunction |
  TensorWriter |
  TensorWriterBinaryBlock |
  TensorWriterBinaryBlockParallel |
  TensorWriterBinaryBlockParallel.WriteFileTask |
  TensorWriterFactory |
  TensorWriterTextCell |
  TensorWriterTextCellParallel |
  Ternary |
  Ternary |
  Ternary | Lop to perform Sum of a matrix with another matrix multiplied by Scalar.
  TernaryAggregate |
  TernaryCPInstruction |
  TernaryFEDInstruction |
  TernaryFrameScalarCPInstruction |
  TernaryFrameScalarFEDInstruction |
  TernaryFrameScalarSPInstruction |
  TernaryOp | Primary use cases for now, are `quantile (<n-1-matrix>, <n-1-matrix>, <literal>): quantile (A, w, 0.5)` `quantile (<n-1-matrix>, <n-1-matrix>, <scalar>): quantile (A, w, s)` `interquantile (<n-1-matrix>, <n-1-matrix>, <scalar>): interquantile (A, w, s)` Keep in mind, that we also have binaries for it w/o weights.
  TernaryOperator |
  TernarySPInstruction |
  TernaryValueFunction |
  TernaryValueFunction.ValueFunctionWithConstant |
  TextToBinaryCellConverter |
  TfMetaUtils |
  TfOffsetMap |
  TfUtils |
  TfUtils.TfMethod |
  Timing | Helper class for encapsulated time measurements.
  Tokenizer |
  TokenizerFactory |
  TokenizerPost |
  TokenizerPostCount |
  TokenizerPostHash |
  TokenizerPostPosition |
  TokenizerPre |
  TokenizerPreNgram |
  TokenizerPreWhitespaceSplit |
  Transform |
  TransformStatistics |
  TriggerBroadcastTask |
  TriggerRemoteOperationsTask |
  TripleIndexes |
  TripleIndexes.Comparator |
  Tsmm2SPInstruction |
  TsmmFEDInstruction |
  TsmmSPInstruction |
  Types |
  Types.AggOp |
  Types.BlockType | Serialization block types (empty, dense, sparse, ultra-sparse)
  Types.CorrectionLocationType |
  Types.DataType | Data types (tensor, matrix, scalar, frame, object, unknown).
  Types.Direction | Type of aggregation direction
  Types.ExecMode | Execution mode for entire script.
  Types.ExecType | Execution type of individual operations.
  Types.FileFormat |
  Types.FunctionBlock | Common type for both function statement blocks and function program blocks
  Types.OpOp1 |
  Types.OpOp2 |
  Types.OpOp3 |
  Types.OpOp4 |
  Types.OpOpData |
  Types.OpOpDG |
  Types.OpOpDnn |
  Types.OpOpN |
  Types.ParamBuiltinOp |
  Types.ReOrgOp |
  Types.ReturnType | Type of builtin or user-defined function with regard to its number of return variables.
  Types.ValueType | Value types (int, double, string, boolean, unknown).
  UAggOuterChain | TODO Currently this lop only support the right hand side in distributed cache.
  UaggOuterChainCPInstruction |
  UaggOuterChainSPInstruction | Two types of broadcast variables used -- 1.
  Unary |
  Unary |
  Unary | Lop to perform following operations: with one operand -- NOT(A), ABS(A), SQRT(A), LOG(A) with two operands where one of them is a scalar -- H=H*i, H=H*5, EXP(A,2), LOG(A,2)
  UnaryCP |
  UnaryCPInstruction |
  UnaryFEDInstruction |
  UnaryFrameCPInstruction |
  UnaryFrameSPInstruction |
  UnaryMatrixCPInstruction |
  UnaryMatrixFEDInstruction |
  UnaryMatrixSPInstruction |
  UnaryOp |
  UnaryOperator |
  UnaryScalarCPInstruction |
  UnarySPInstruction |
  UnifiedMemoryAllocator |
  UnifiedMemoryManager | Unified Memory Manager - Initial Design Motivation: The Unified Memory Manager, henceforth UMM, will act as a central manager of in-memory matrix (uncompressed and compressed), frame, and tensor blocks within SystemDS control program.
  UniformPRNGenerator |
  Util |
  UtilFunctions |
  Utils |
  ValueComparisonFunction | Abstraction for comparison (relational) operators in order to force a proper implementation by all relevant subclasses.
  ValueFunction |
  ValueTrimFormat |
  VariableCPInstruction |
  VariableCPInstruction.VariableOperationCode |
  VariableFEDInstruction |
  VariableSet |
  VarStats |
  Warnings |
  WeightedCell |
  WeightedCrossEntropy |
  WeightedCrossEntropy.WCeMMType |
  WeightedCrossEntropyR |
  WeightedDivMM |
  WeightedDivMM.WDivMMType |
  WeightedDivMMR |
  WeightedPair |
  WeightedSigmoid |
  WeightedSigmoid.WSigmoidType |
  WeightedSigmoidR |
  WeightedSquaredLoss |
  WeightedSquaredLoss.WeightsType |
  WeightedSquaredLossR |
  WeightedUnaryMM |
  WeightedUnaryMM.WUMMType |
  WeightedUnaryMMR |
  WhileProgramBlock |
  WhileStatement |
  WhileStatementBlock |
  WorkerController |
  WorkerService |
  WorkloadAnalyzer |
  WriterBinaryBlock |
  WriterBinaryBlockParallel |
  WriterHDF5 |
  WriterHDF5Parallel |
  WriterMatrixMarket |
  WriterMatrixMarketParallel |
  WriterTextCell |
  WriterTextCellParallel |
  WriterTextCSV |
  WriterTextCSVParallel |
  WriterTextLIBSVM |
  WriterTextLIBSVMParallel |
  WriteSPInstruction |
  WTreeNode | A Node in the WTree, this is used for any nodes that are not the root.
  WTreeRoot | The root node of the tree, located at the top of the tree.
  Xor |
  ZipmmSPInstruction |