## Uses of Class
org.apache.sysds.common.Types.ValueType

Packages that use Types.ValueType
org.apache.sysds.api.jmlc
org.apache.sysds.api.mlcontext
org.apache.sysds.common
org.apache.sysds.hops
org.apache.sysds.hops.codegen
org.apache.sysds.hops.rewrite
org.apache.sysds.lops
org.apache.sysds.parser
org.apache.sysds.runtime.controlprogram
org.apache.sysds.runtime.controlprogram.caching
org.apache.sysds.runtime.controlprogram.context
org.apache.sysds.runtime.data
org.apache.sysds.runtime.instructions
org.apache.sysds.runtime.instructions.cp
org.apache.sysds.runtime.instructions.spark.data
org.apache.sysds.runtime.instructions.spark.utils
org.apache.sysds.runtime.io
org.apache.sysds.runtime.matrix.data
org.apache.sysds.runtime.transform.decode
org.apache.sysds.runtime.transform.encode
org.apache.sysds.runtime.transform.tokenize
org.apache.sysds.runtime.util

### Uses of Types.ValueType in org.apache.sysds.api.jmlc

Method parameters in org.apache.sysds.api.jmlc with type arguments of type Types.ValueType
`void` PreparedScript.`setFrame(String varname, String[][] frame, List<Types.ValueType> schema)` Binds a frame object to a registered input variable.
`void` PreparedScript.`setFrame(String varname, String[][] frame, List<Types.ValueType> schema, boolean reuse)` Binds a frame object to a registered input variable.
`void` PreparedScript.`setFrame(String varname, String[][] frame, List<Types.ValueType> schema, List<String> colnames)` Binds a frame object to a registered input variable.
`void` PreparedScript.`setFrame(String varname, String[][] frame, List<Types.ValueType> schema, List<String> colnames, boolean reuse)` Binds a frame object to a registered input variable.

### Uses of Types.ValueType in org.apache.sysds.api.mlcontext

Methods in org.apache.sysds.api.mlcontext that return types with arguments of type Types.ValueType
`List<Types.ValueType>` FrameSchema.`getSchema()` Obtain the frame schema

Method parameters in org.apache.sysds.api.mlcontext with type arguments of type Types.ValueType
`void` FrameSchema.`setSchema(List<Types.ValueType> schema)` Set the frame schema

Constructor parameters in org.apache.sysds.api.mlcontext with type arguments of type Types.ValueType
Constructor and Description
`FrameSchema(List<Types.ValueType> schema)` Constructor that specifies the schema as a list of `ValueType` values.

### Uses of Types.ValueType in org.apache.sysds.common

Methods in org.apache.sysds.common that return Types.ValueType
`static Types.ValueType` Types.ValueType.`fromExternalString(String value)`
`static Types.ValueType` Types.ValueType.`valueOf(String name)` Returns the enum constant of this type with the specified name.
`static Types.ValueType[]` Types.ValueType.`values()` Returns an array containing the constants of this enum type, in the order they are declared.

### Uses of Types.ValueType in org.apache.sysds.hops

Methods in org.apache.sysds.hops that return Types.ValueType
`Types.ValueType` Hop.`getValueType()`

Methods in org.apache.sysds.hops with parameters of type Types.ValueType
`static Lop` BinaryOp.`constructSPAppendLop(Hop left, Hop right, Types.DataType dt, Types.ValueType vt, boolean cbind, Hop current)`
`static boolean` OptimizerUtils.`isValidCPDimensions(Types.ValueType[] schema, String[] names)` Returns false if schema and names are not properly specified; other true Length to be > 0, and length of both to be equal.
`void` Hop.`setValueType(Types.ValueType vt)`

Constructors in org.apache.sysds.hops with parameters of type Types.ValueType
Constructor and Description
`AggBinaryOp(String l, Types.DataType dt, Types.ValueType vt, Types.OpOp2 innOp, Types.AggOp outOp, Hop in1, Hop in2)`
`AggUnaryOp(String l, Types.DataType dt, Types.ValueType vt, Types.AggOp o, Types.Direction idx, Hop inp)`
`BinaryOp(String l, Types.DataType dt, Types.ValueType vt, Types.OpOp2 o, Hop inp1, Hop inp2)`
`DataOp(String l, Types.DataType dt, Types.ValueType vt, Hop in, Types.OpOpData dop, String fname)`
`DataOp(String l, Types.DataType dt, Types.ValueType vt, Types.OpOpData dop, HashMap<String,Hop> params)` READ operation for Matrix / SQL operation for tensor This constructor supports expressions in parameters
`DataOp(String l, Types.DataType dt, Types.ValueType vt, Types.OpOpData dop, Hop in, HashMap<String,Hop> inputParameters)` WRITE operation for Matrix This constructor supports expression in parameters
`DataOp(String l, Types.DataType dt, Types.ValueType vt, Types.OpOpData dop, String fname, long dim1, long dim2, long nnz, int blen)` READ operation for Matrix w/ dim1, dim2.
`DataOp(String l, Types.DataType dt, Types.ValueType vt, Types.OpOpData dop, String fname, long dim1, long dim2, long nnz, MatrixObject.UpdateType update, int blen)`
`DnnOp(String l, Types.DataType dt, Types.ValueType vt, Types.OpOpDnn o, ArrayList<Hop> inp)` Create a hop from the builtin expression
`Hop(String l, Types.DataType dt, Types.ValueType vt)`
`IndexingOp(String l, Types.DataType dt, Types.ValueType vt, Hop inpMatrix, Hop inpRowL, Hop inpRowU, Hop inpColL, Hop inpColU, boolean passedRowsLEU, boolean passedColsLEU)`
`LeftIndexingOp(String l, Types.DataType dt, Types.ValueType vt, Hop inpMatrixLeft, Hop inpMatrixRight, Hop inpRowL, Hop inpRowU, Hop inpColL, Hop inpColU, boolean passedRowsLEU, boolean passedColsLEU)`
`MultiThreadedHop(String name, Types.DataType dt, Types.ValueType vt)`
`NaryOp(String name, Types.DataType dataType, Types.ValueType valueType, Types.OpOpN op, Hop... inputs)` NaryOp constructor.
`ParameterizedBuiltinOp(String l, Types.DataType dt, Types.ValueType vt, Types.ParamBuiltinOp op, LinkedHashMap<String,Hop> inputParameters)` Creates a new HOP for a function call
`QuaternaryOp(String l, Types.DataType dt, Types.ValueType vt, Types.OpOp4 o, Hop inX, Hop inU, Hop inV)`
`QuaternaryOp(String l, Types.DataType dt, Types.ValueType vt, Types.OpOp4 o, Hop inX, Hop inU, Hop inV, boolean flag1, boolean flag2)` Constructor for wsigmoid.
`QuaternaryOp(String l, Types.DataType dt, Types.ValueType vt, Types.OpOp4 o, Hop inW, Hop inU, Hop inV, boolean umult, Types.OpOp1 uop, Types.OpOp2 sop)`
`QuaternaryOp(String l, Types.DataType dt, Types.ValueType vt, Types.OpOp4 o, Hop inX, Hop inU, Hop inV, Hop inW, boolean post)` Constructor for wsloss.
`QuaternaryOp(String l, Types.DataType dt, Types.ValueType vt, Types.OpOp4 o, Hop inX, Hop inU, Hop inV, Hop inW, int baseType, boolean flag1, boolean flag2)`
`ReorgOp(String l, Types.DataType dt, Types.ValueType vt, Types.ReOrgOp o, ArrayList<Hop> inp)`
`ReorgOp(String l, Types.DataType dt, Types.ValueType vt, Types.ReOrgOp o, Hop inp)`
`TernaryOp(String l, Types.DataType dt, Types.ValueType vt, Types.OpOp3 o, Hop inp1, Hop inp2, Hop inp3)`
`TernaryOp(String l, Types.DataType dt, Types.ValueType vt, Types.OpOp3 o, Hop inp1, Hop inp2, Hop inp3, Hop inp4, Hop inp5, Hop inp6)`
`UnaryOp(String l, Types.DataType dt, Types.ValueType vt, Types.OpOp1 o, Hop inp)`

### Uses of Types.ValueType in org.apache.sysds.hops.codegen

Constructors in org.apache.sysds.hops.codegen with parameters of type Types.ValueType
Constructor and Description
`SpoofFusedOp(String name, Types.DataType dt, Types.ValueType vt, Class<?> cla, SpoofCompiler.GeneratorAPI api, String genVarName, boolean dist, SpoofFusedOp.SpoofOutputDimsType type)`

### Uses of Types.ValueType in org.apache.sysds.hops.rewrite

Methods in org.apache.sysds.hops.rewrite with parameters of type Types.ValueType
`static Hop` HopRewriteUtils.`createDataGenOpByVal(Hop rowInput, Hop colInput, Hop dimsInput, Types.DataType dt, Types.ValueType vt, double value)`

### Uses of Types.ValueType in org.apache.sysds.lops

Methods in org.apache.sysds.lops that return Types.ValueType
`Types.ValueType` Lop.`getValueType()` get value type of the output that is produced by this lop

Methods in org.apache.sysds.lops with parameters of type Types.ValueType
`static SortKeys` SortKeys.`constructSortByValueLop(Lop input1, Lop input2, SortKeys.OperationTypes op, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
`static SortKeys` SortKeys.`constructSortByValueLop(Lop input1, SortKeys.OperationTypes op, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
`static Data` Data.`createLiteralLop(Types.ValueType vt, String literalValue)` Method to create literal LOPs.
`void` AppendG.`init(Lop input1, Lop input2, Lop input3, Lop input4, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
`void` AppendGAlignedSP.`init(Lop input1, Lop input2, Lop input3, Types.DataType dt, Types.ValueType vt)`
`void` Append.`init(Lop input1, Lop input2, Lop input3, Types.DataType dt, Types.ValueType vt)`
`void` AppendM.`init(Lop input1, Lop input2, Lop input3, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
`void` AppendR.`init(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
`String` Lop.`prepOperand(String label, Types.DataType dt, Types.ValueType vt)` Method to prepare instruction operand with given parameters.
`String` Lop.`prepOperand(String label, Types.DataType dt, Types.ValueType vt, boolean literal)` Method to prepare instruction operand with given parameters.
`void` Lop.`setValueType(Types.ValueType vt)` set value type of the output that is produced by this lop

Constructors in org.apache.sysds.lops with parameters of type Types.ValueType
Constructor and Description
`Append(Lop input1, Lop input2, Lop input3, Types.DataType dt, Types.ValueType vt, boolean cbind, Types.ExecType et)`
`AppendG(Lop input1, Lop input2, Lop input3, Lop input4, Types.DataType dt, Types.ValueType vt, boolean cbind, Types.ExecType et)`
`AppendGAlignedSP(Lop input1, Lop input2, Lop input3, Types.DataType dt, Types.ValueType vt, boolean cbind)`
`AppendM(Lop input1, Lop input2, Lop input3, Types.DataType dt, Types.ValueType vt, boolean cbind, boolean partitioned, Types.ExecType et)`
`AppendR(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, boolean cbind, Types.ExecType et)`
`Binary(Lop input1, Lop input2, Types.OpOp2 op, Types.DataType dt, Types.ValueType vt, Types.ExecType et)` Constructor to perform a binary operation.
`Binary(Lop input1, Lop input2, Types.OpOp2 op, Types.DataType dt, Types.ValueType vt, Types.ExecType et, int k)`
`BinaryM(Lop input1, Lop input2, Types.OpOp2 op, Types.DataType dt, Types.ValueType vt, Types.ExecType et, boolean colVector)` Constructor to perform a binary operation.
`BinaryScalar(Lop input1, Lop input2, Types.OpOp2 op, Types.DataType dt, Types.ValueType vt)` Constructor to perform a scalar operation
`BinaryUAggChain(Lop input1, Types.OpOp2 bop, Types.AggOp uaop, Types.Direction uadir, Types.DataType dt, Types.ValueType vt, Types.ExecType et)` Constructor to setup a map mult chain without weights
`CentralMoment(Lop input1, Lop input2, Lop input3, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
`CentralMoment(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
`Checkpoint(Lop input, Types.DataType dt, Types.ValueType vt, String level)` TODO change string parameter storage.level to StorageLevel as soon as we can assume that Spark libraries are always available.
`Compression(Lop input, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
`CoVariance(Lop input1, Lop input2, Lop input3, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
`CoVariance(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
`CoVariance(Lop input1, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
`CSVReBlock(Lop input, int blen, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
`Ctable(Lop[] inputLops, Ctable.OperationTypes op, Types.DataType dt, Types.ValueType vt, boolean ignoreZeros, boolean outputEmptyBlocks, Types.ExecType et)`
`Ctable(Lop[] inputLops, Ctable.OperationTypes op, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
`CumulativeOffsetBinary(Lop data, Lop offsets, Types.DataType dt, Types.ValueType vt, double init, boolean broadcast, Types.AggOp op, Types.ExecType et)`
`CumulativeOffsetBinary(Lop data, Lop offsets, Types.DataType dt, Types.ValueType vt, Types.AggOp op, Types.ExecType et)`
`CumulativePartialAggregate(Lop input, Types.DataType dt, Types.ValueType vt, Types.AggOp op, Types.ExecType et)`
`Data(Types.OpOpData op, Lop input, HashMap<String,Lop> inputParametersLops, String name, String literal, Types.DataType dt, Types.ValueType vt, Types.FileFormat fmt)` Constructor to setup read or write LOP In case of write: `input` must be provided.
`DataGen(Types.OpOpDG op, DataIdentifier id, HashMap<String,Lop> inputParametersLops, String baseDir, Types.DataType dt, Types.ValueType vt, Types.ExecType et)` Creates a new Rand-LOP.
`DeCompression(Lop input, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
`DnnTransform(Lop input1, Lop input2, Lop input3, Types.OpOpDnn op, Types.DataType dt, Types.ValueType vt, Types.ExecType et, int k)`
`DnnTransform(Lop input1, Lop input2, Types.OpOpDnn op, Types.DataType dt, Types.ValueType vt, Types.ExecType et, int k)`
`DnnTransform(Lop input, Types.OpOpDnn op, Types.DataType dt, Types.ValueType vt, Types.ExecType et, int k, double intermediateMemBudget)` Constructor when we have one input.
`Federated(HashMap<String,Lop> inputLops, Types.DataType dataType, Types.ValueType valueType)`
`GroupedAggregate(HashMap<String,Lop> inputParameterLops, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
`GroupedAggregate(HashMap<String,Lop> inputParameterLops, Types.DataType dt, Types.ValueType vt, Types.ExecType et, boolean broadcastGroups)`
`GroupedAggregate(HashMap<String,Lop> inputParameterLops, Types.DataType dt, Types.ValueType vt, Types.ExecType et, int k)`
`GroupedAggregateM(HashMap<String,Lop> inputParameterLops, Types.DataType dt, Types.ValueType vt, boolean partitioned, Types.ExecType et)`
`LeftIndex(Lop lhsInput, Lop rhsInput, Lop rowL, Lop rowU, Lop colL, Lop colU, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
`LeftIndex(Lop lhsInput, Lop rhsInput, Lop rowL, Lop rowU, Lop colL, Lop colU, Types.DataType dt, Types.ValueType vt, Types.ExecType et, LeftIndex.LixCacheType type)`
`Lop(Lop.Type t, Types.DataType dt, Types.ValueType vt)` Constructor to be invoked by base class.
`MapMult(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, boolean rightCache, boolean partitioned, boolean emptyBlocks, AggBinaryOp.SparkAggType aggtype)` Constructor to setup a partial Matrix-Vector Multiplication for Spark
`MapMultChain(Lop input1, Lop input2, Lop input3, MapMultChain.ChainType chain, Types.DataType dt, Types.ValueType vt, Types.ExecType et)` Constructor to setup a map mult chain with weights
`MapMultChain(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, Types.ExecType et)` Constructor to setup a map mult chain without weights
`MatMultCP(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
`MatMultCP(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, Types.ExecType et, boolean isLeftTransposed, boolean isRightTransposed)`
`MatMultCP(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, Types.ExecType et, int k)`
`MatMultCP(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, Types.ExecType et, int k, boolean isLeftTransposed, boolean isRightTransposed)`
`MMCJ(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, boolean outputEmptyBlocks, AggBinaryOp.SparkAggType aggtype, Types.ExecType et)`
`MMCJ(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, MMCJ.MMCJType type, Types.ExecType et)` Constructor to perform a cross product operation.
`MMRJ(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, Types.ExecType et)` Constructor to perform a cross product operation.
`MMTSJ(Lop input1, Types.DataType dt, Types.ValueType vt, Types.ExecType et, MMTSJ.MMTSJType type)`
`MMTSJ(Lop input1, Types.DataType dt, Types.ValueType vt, Types.ExecType et, MMTSJ.MMTSJType type, boolean multiPass)`
`MMTSJ(Lop input1, Types.DataType dt, Types.ValueType vt, Types.ExecType et, MMTSJ.MMTSJType type, boolean multiPass, int k)`
`MMZip(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, boolean tRewrite, Types.ExecType et)`
`Nary(Types.OpOpN operationType, Types.DataType dt, Types.ValueType vt, Lop[] inputLops, Types.ExecType et)`
`ParameterizedBuiltin(HashMap<String,Lop> paramLops, Types.ParamBuiltinOp op, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
`ParameterizedBuiltin(HashMap<String,Lop> paramLops, Types.ParamBuiltinOp op, Types.DataType dt, Types.ValueType vt, Types.ExecType et, boolean bRmEmptyBC)`
`ParameterizedBuiltin(HashMap<String,Lop> paramLops, Types.ParamBuiltinOp op, Types.DataType dt, Types.ValueType vt, Types.ExecType et, int k)`
`PartialAggregate(Lop input, Types.AggOp op, Types.Direction direct, Types.DataType dt, Types.ValueType vt, AggBinaryOp.SparkAggType aggtype, Types.ExecType et)`
`PartialAggregate(Lop input, Types.AggOp op, Types.Direction direct, Types.DataType dt, Types.ValueType vt, Types.ExecType et, int k)`
`PickByCount(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, PickByCount.OperationTypes op, Types.ExecType et)`
`PickByCount(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, PickByCount.OperationTypes op, Types.ExecType et, boolean inMemoryInput)`
`PMapMult(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt)`
`PMMJ(Lop pminput, Lop rightinput, Lop nrow, Types.DataType dt, Types.ValueType vt, boolean partitioned, boolean emptyBlocks, Types.ExecType et)` Constructor to setup a Permutation Matrix Multiplication
`ReBlock(Lop input, int blen, Types.DataType dt, Types.ValueType vt, boolean outputEmptyBlocks, Types.ExecType et)`
`RightIndex(Lop input, Lop rowL, Lop rowU, Lop colL, Lop colU, Lop rowDim, Lop colDim, Types.DataType dt, Types.ValueType vt, AggBinaryOp.SparkAggType aggtype, Types.ExecType et)`
`RightIndex(Lop input, Lop rowL, Lop rowU, Lop colL, Lop colU, Lop rowDim, Lop colDim, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
`RightIndex(Lop input, Lop rowL, Lop rowU, Lop colL, Lop colU, Lop rowDim, Lop colDim, Types.DataType dt, Types.ValueType vt, Types.ExecType et, boolean forleft)`
`SortKeys(Lop input, boolean desc, SortKeys.OperationTypes op, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
`SortKeys(Lop input1, Lop input2, SortKeys.OperationTypes op, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
`SortKeys(Lop input, SortKeys.OperationTypes op, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
`SpoofFused(ArrayList<Lop> inputs, Types.DataType dt, Types.ValueType vt, Class<?> cla, SpoofCompiler.GeneratorAPI api, String genVarName, int k, Types.ExecType etype)`
`Sql(HashMap<String,Lop> inputParametersLops, Types.DataType dt, Types.ValueType vt)`
`Ternary(Types.OpOp3 op, Lop input1, Lop input2, Lop input3, Types.DataType dt, Types.ValueType vt, Types.ExecType et, int numThreads)`
`TernaryAggregate(Lop input1, Lop input2, Lop input3, Types.AggOp aggOp, Types.OpOp2 binOp, Types.Direction direction, Types.DataType dt, Types.ValueType vt, Types.ExecType et, int k)`
`Transform(Lop[] inputs, Types.ReOrgOp op, Types.DataType dt, Types.ValueType vt, boolean outputEmptyBlock, Types.ExecType et)`
`Transform(Lop[] inputs, Types.ReOrgOp op, Types.DataType dt, Types.ValueType vt, Types.ExecType et, boolean bSortIndInMem)`
`Transform(Lop[] inputs, Types.ReOrgOp op, Types.DataType dt, Types.ValueType vt, Types.ExecType et, boolean bSortIndInMem, int k)`
`Transform(Lop[] inputs, Types.ReOrgOp op, Types.DataType dt, Types.ValueType vt, Types.ExecType et, int k)`
`Transform(Lop input, Types.ReOrgOp op, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
`Transform(Lop input, Types.ReOrgOp op, Types.DataType dt, Types.ValueType vt, Types.ExecType et, boolean bSortIndInMem)`
`Transform(Lop input, Types.ReOrgOp op, Types.DataType dt, Types.ValueType vt, Types.ExecType et, int k)`
`UAggOuterChain(Lop input1, Lop input2, Types.AggOp uaop, Types.Direction uadir, Types.OpOp2 bop, Types.DataType dt, Types.ValueType vt, Types.ExecType et)` Constructor to setup a unaryagg outer chain
`Unary(Lop input1, Lop input2, Types.OpOp1 op, Types.DataType dt, Types.ValueType vt, Types.ExecType et, int numThreads)` Constructor to perform a unary operation with 2 inputs
`Unary(Lop input1, Types.OpOp1 op, Types.DataType dt, Types.ValueType vt, Types.ExecType et, int numThreads, boolean inplace)` Constructor to perform a unary operation with 1 input.
`UnaryCP(Lop input, Types.OpOp1 op, Types.DataType dt, Types.ValueType vt)`
`UnaryCP(Lop input, Types.OpOp1 op, Types.DataType dt, Types.ValueType vt, Types.ExecType et)` Constructor to perform a scalar operation
`WeightedCrossEntropy(Lop input1, Lop input2, Lop input3, Lop input4, Types.DataType dt, Types.ValueType vt, WeightedCrossEntropy.WCeMMType wt, Types.ExecType et)`
`WeightedCrossEntropyR(Lop input1, Lop input2, Lop input3, Lop input4, Types.DataType dt, Types.ValueType vt, WeightedCrossEntropy.WCeMMType wt, boolean cacheU, boolean cacheV, Types.ExecType et)`
`WeightedDivMM(Lop input1, Lop input2, Lop input3, Lop input4, Types.DataType dt, Types.ValueType vt, WeightedDivMM.WDivMMType wt, Types.ExecType et)`
`WeightedDivMMR(Lop input1, Lop input2, Lop input3, Lop input4, Types.DataType dt, Types.ValueType vt, WeightedDivMM.WDivMMType wt, boolean cacheU, boolean cacheV, Types.ExecType et)`
`WeightedSigmoid(Lop input1, Lop input2, Lop input3, Types.DataType dt, Types.ValueType vt, WeightedSigmoid.WSigmoidType wt, Types.ExecType et)`
`WeightedSigmoidR(Lop input1, Lop input2, Lop input3, Types.DataType dt, Types.ValueType vt, WeightedSigmoid.WSigmoidType wt, boolean cacheU, boolean cacheV, Types.ExecType et)`
`WeightedSquaredLoss(Lop input1, Lop input2, Lop input3, Lop input4, Types.DataType dt, Types.ValueType vt, WeightedSquaredLoss.WeightsType wt, Types.ExecType et)`
`WeightedSquaredLossR(Lop input1, Lop input2, Lop input3, Lop input4, Types.DataType dt, Types.ValueType vt, WeightedSquaredLoss.WeightsType wt, boolean cacheU, boolean cacheV, Types.ExecType et)`
`WeightedUnaryMM(Lop input1, Lop input2, Lop input3, Types.DataType dt, Types.ValueType vt, WeightedUnaryMM.WUMMType wt, Types.OpOp1 op, Types.ExecType et)`
`WeightedUnaryMMR(Lop input1, Lop input2, Lop input3, Types.DataType dt, Types.ValueType vt, WeightedUnaryMM.WUMMType wt, Types.OpOp1 op, boolean cacheU, boolean cacheV, Types.ExecType et)`

### Uses of Types.ValueType in org.apache.sysds.parser

Methods in org.apache.sysds.parser that return Types.ValueType
`static Types.ValueType` Expression.`computeValueType(Expression expression1, Expression expression2, boolean cast)` Compute value type based on expressions.
`static Types.ValueType` Expression.`computeValueType(Expression expr1, Types.ValueType v1, Types.ValueType v2, boolean cast)`
`static Types.ValueType` Expression.`computeValueType(Identifier identifier1, Identifier identifier2, boolean cast)` Compute value type based on identifiers.
`Types.ValueType` Identifier.`getValueType()`

Methods in org.apache.sysds.parser with parameters of type Types.ValueType
`static Types.ValueType` Expression.`computeValueType(Expression expr1, Types.ValueType v1, Types.ValueType v2, boolean cast)`
`static Builtins` BuiltinFunctionExpression.`getValueTypeCastOperator(Types.ValueType vt)` Convert a value type (double, int, or boolean) to a built-in function operator.
`void` Identifier.`setValueType(Types.ValueType vt)`

Constructors in org.apache.sysds.parser with parameters of type Types.ValueType
Constructor and Description
`DataIdentifier(String name, Types.DataType dt, Types.ValueType vt)`

### Uses of Types.ValueType in org.apache.sysds.runtime.controlprogram

Methods in org.apache.sysds.runtime.controlprogram with parameters of type Types.ValueType
`ScalarObject` ProgramBlock.`executePredicate(ArrayList<Instruction> inst, Hop hops, boolean requiresRecompile, Types.ValueType retType, ExecutionContext ec)` Executes given predicate instructions (incl recompilation if required)

### Uses of Types.ValueType in org.apache.sysds.runtime.controlprogram.caching

Methods in org.apache.sysds.runtime.controlprogram.caching that return Types.ValueType
`Types.ValueType[]` FrameObject.`getSchema()`
`Types.ValueType[]` FrameObject.`getSchema(int cl, int cu)` Obtain schema of value types
`Types.ValueType[]` FrameObject.`mergeSchemas(FrameObject fo)` Creates a new collection which contains the schema of the current frame object concatenated with the schema of the passed frame object.

Methods in org.apache.sysds.runtime.controlprogram.caching with parameters of type Types.ValueType
`void` FrameObject.`setSchema(Types.ValueType[] schema)`

Constructors in org.apache.sysds.runtime.controlprogram.caching with parameters of type Types.ValueType
Constructor and Description
`FrameObject(String fname, MetaData meta, Types.ValueType[] schema)`
`MatrixObject(Types.ValueType vt, String file)` Constructor that takes the value type and the HDFS filename.
`MatrixObject(Types.ValueType vt, String file, MetaData mtd)` Constructor that takes the value type, HDFS filename and associated metadata.
`MatrixObject(Types.ValueType vt, String file, MetaData mtd, MatrixBlock data)` Constructor that takes the value type, HDFS filename and associated metadata and a MatrixBlock used for creation after serialization
`TensorObject(Types.ValueType vt, String fname)`

### Uses of Types.ValueType in org.apache.sysds.runtime.controlprogram.context

Methods in org.apache.sysds.runtime.controlprogram.context with parameters of type Types.ValueType
`ScalarObject` ExecutionContext.`getScalarInput(String name, Types.ValueType vt, boolean isLiteral)`
`static FrameBlock` SparkExecutionContext.`toFrameBlock(org.apache.spark.api.java.JavaPairRDD<Long,FrameBlock> rdd, Types.ValueType[] schema, int rlen, int clen)`
`static FrameBlock` SparkExecutionContext.`toFrameBlock(RDDObject rdd, Types.ValueType[] schema, int rlen, int clen)`

### Uses of Types.ValueType in org.apache.sysds.runtime.data

Fields in org.apache.sysds.runtime.data declared as Types.ValueType
`static Types.ValueType` TensorBlock.`DEFAULT_VTYPE`

Methods in org.apache.sysds.runtime.data that return Types.ValueType
`Types.ValueType` DataTensorBlock.`getColValueType(int col)`
`Types.ValueType[]` DataTensorBlock.`getSchema()`
`Types.ValueType[]` TensorBlock.`getSchema()` Get the schema if this `TensorBlock` is heterogeneous.
`Types.ValueType` TensorBlock.`getValueType()` Get the `ValueType` if this `TensorBlock` is homogeneous.
`Types.ValueType` BasicTensorBlock.`getValueType()`
`static Types.ValueType` TensorBlock.`resultValueType(Types.ValueType in1, Types.ValueType in2)`

Methods in org.apache.sysds.runtime.data with parameters of type Types.ValueType
`static DenseBlock` DenseBlockFactory.`createDenseBlock(Types.ValueType vt, DenseBlock.Type type, int[] dims)`
`static DenseBlock` DenseBlockFactory.`createDenseBlock(Types.ValueType vt, int[] dims)`
`void` DataTensorBlock.`reset(int[] dims, Types.ValueType[] schema)`
`static Types.ValueType` TensorBlock.`resultValueType(Types.ValueType in1, Types.ValueType in2)`

Constructors in org.apache.sysds.runtime.data with parameters of type Types.ValueType
Constructor and Description
`BasicTensorBlock(int[] dims, Types.ValueType vt, double val)`
`BasicTensorBlock(Types.ValueType vt, int[] dims)`
`BasicTensorBlock(Types.ValueType vt, int[] dims, boolean sp)`
`BasicTensorBlock(Types.ValueType vt, int[] dims, boolean sp, long estnnz)`
`DataTensorBlock(int ncols, Types.ValueType vt)`
`DataTensorBlock(Types.ValueType[] schema)`
`DataTensorBlock(Types.ValueType[] schema, int[] dims)`
`DataTensorBlock(Types.ValueType[] schema, int[] dims, String[][] data)`
`DataTensorBlock(Types.ValueType vt, int[] dims)`
`TensorBlock(Types.ValueType[] schema, int[] dims)` Create a data `TensorBlock` with the given schema and the given dimensions.
`TensorBlock(Types.ValueType vt, int[] dims)` Create a basic `TensorBlock` with the given `ValueType` and the given dimensions.

### Uses of Types.ValueType in org.apache.sysds.runtime.instructions

Methods in org.apache.sysds.runtime.instructions with parameters of type Types.ValueType
`static String` InstructionUtils.`createLiteralOperand(String val, Types.ValueType vt)`

### Uses of Types.ValueType in org.apache.sysds.runtime.instructions.cp

Methods in org.apache.sysds.runtime.instructions.cp that return Types.ValueType
`Types.ValueType` CPOperand.`getValueType()`
`Types.ValueType` Data.`getValueType()`

Methods in org.apache.sysds.runtime.instructions.cp with parameters of type Types.ValueType
`static LiteralOp` ScalarObjectFactory.`createLiteralOp(Types.ValueType vt, String value)`
`static ScalarObject` ScalarObjectFactory.`createScalarObject(Types.ValueType vt, double value)`
`static ScalarObject` ScalarObjectFactory.`createScalarObject(Types.ValueType vt, LiteralOp lit)`
`static ScalarObject` ScalarObjectFactory.`createScalarObject(Types.ValueType vt, Object obj)`
`static ScalarObject` ScalarObjectFactory.`createScalarObject(Types.ValueType vt, ScalarObject so)`
`static ScalarObject` ScalarObjectFactory.`createScalarObject(Types.ValueType vt, String value)`

Constructors in org.apache.sysds.runtime.instructions.cp with parameters of type Types.ValueType
Constructor and Description
`CPOperand(String name, Types.ValueType vt, Types.DataType dt)`
`CPOperand(String name, Types.ValueType vt, Types.DataType dt, boolean literal)`
`ScalarObject(Types.ValueType vt)`

### Uses of Types.ValueType in org.apache.sysds.runtime.instructions.spark.data

Constructors in org.apache.sysds.runtime.instructions.spark.data with parameters of type Types.ValueType
Constructor and Description
`FrameReblockBuffer(int buffersize, long rlen, long clen, Types.ValueType[] schema)`

### Uses of Types.ValueType in org.apache.sysds.runtime.instructions.spark.utils

Methods in org.apache.sysds.runtime.instructions.spark.utils with parameters of type Types.ValueType
`static org.apache.spark.sql.Dataset<org.apache.spark.sql.Row>` FrameRDDConverterUtils.`binaryBlockToDataFrame(org.apache.spark.sql.SparkSession sparkSession, org.apache.spark.api.java.JavaPairRDD<Long,FrameBlock> in, DataCharacteristics mc, Types.ValueType[] schema)`
`static org.apache.spark.sql.Dataset<org.apache.spark.sql.Row>` FrameRDDConverterUtils.`binaryBlockToDataFrame(org.apache.spark.sql.SQLContext sqlContext, org.apache.spark.api.java.JavaPairRDD<Long,FrameBlock> in, DataCharacteristics mc, Types.ValueType[] schema)` Deprecated.
`static int` FrameRDDConverterUtils.`convertDFSchemaToFrameSchema(org.apache.spark.sql.types.StructType dfschema, String[] colnames, Types.ValueType[] fschema, boolean containsID)` NOTE: regarding the support of vector columns, we make the following schema restriction: single vector column, which allows inference of the vector length without data access and covers the common case.
`static org.apache.spark.sql.types.StructType` FrameRDDConverterUtils.`convertFrameSchemaToDFSchema(Types.ValueType[] fschema, boolean containsID)` This function will convert Frame schema into DataFrame schema
`static org.apache.spark.api.java.JavaPairRDD<Long,FrameBlock>` FrameRDDConverterUtils.`csvToBinaryBlock(org.apache.spark.api.java.JavaSparkContext sc, org.apache.spark.api.java.JavaPairRDD<org.apache.hadoop.io.LongWritable,org.apache.hadoop.io.Text> input, DataCharacteristics mc, Types.ValueType[] schema, boolean hasHeader, String delim, boolean fill, double fillValue, Set<String> naStrings)`
`static org.apache.spark.api.java.JavaPairRDD<Long,FrameBlock>` FrameRDDConverterUtils.`csvToBinaryBlock(org.apache.spark.api.java.JavaSparkContext sc, org.apache.spark.api.java.JavaRDD<String> input, DataCharacteristics mcOut, Types.ValueType[] schema, boolean hasHeader, String delim, boolean fill, double fillValue, Set<String> naStrings)`
`static org.apache.spark.api.java.JavaRDD<org.apache.spark.sql.Row>` FrameRDDConverterUtils.`csvToRowRDD(org.apache.spark.api.java.JavaSparkContext sc, org.apache.spark.api.java.JavaRDD<String> dataRdd, String delim, Types.ValueType[] schema)`
`static org.apache.spark.api.java.JavaRDD<org.apache.spark.sql.Row>` FrameRDDConverterUtils.`csvToRowRDD(org.apache.spark.api.java.JavaSparkContext sc, String fnameIn, String delim, Types.ValueType[] schema)`
`static org.apache.spark.api.java.JavaPairRDD<Long,FrameBlock>` FrameRDDConverterUtils.`textCellToBinaryBlock(org.apache.spark.api.java.JavaSparkContext sc, org.apache.spark.api.java.JavaPairRDD<org.apache.hadoop.io.LongWritable,org.apache.hadoop.io.Text> in, DataCharacteristics mcOut, Types.ValueType[] schema)`
`static org.apache.spark.api.java.JavaPairRDD<Long,FrameBlock>` FrameRDDConverterUtils.`textCellToBinaryBlockLongIndex(org.apache.spark.api.java.JavaSparkContext sc, org.apache.spark.api.java.JavaPairRDD<Long,org.apache.hadoop.io.Text> input, DataCharacteristics mc, Types.ValueType[] schema)`

### Uses of Types.ValueType in org.apache.sysds.runtime.io

Methods in org.apache.sysds.runtime.io that return Types.ValueType
`Types.ValueType[]` FrameReader.`getDefSchema(long clen)`

Methods in org.apache.sysds.runtime.io with parameters of type Types.ValueType
`static FrameBlock[]` FrameWriter.`createFrameBlocksForReuse(Types.ValueType[] schema, String[] names, long rlen)`
`FrameBlock` FrameReader.`readFrameFromHDFS(String fname, Types.ValueType[] schema, long rlen, long clen)`
`FrameBlock` FrameReaderJSONL.`readFrameFromHDFS(String fname, Types.ValueType[] schema, Map<String,Integer> schemaMap, long rlen, long clen)`
`FrameBlock` FrameReaderTextCell.`readFrameFromHDFS(String fname, Types.ValueType[] schema, String[] names, long rlen, long clen)`
`abstract FrameBlock` FrameReader.`readFrameFromHDFS(String fname, Types.ValueType[] schema, String[] names, long rlen, long clen)`
`FrameBlock` FrameReaderTextCSV.`readFrameFromHDFS(String fname, Types.ValueType[] schema, String[] names, long rlen, long clen)`
`FrameBlock` FrameReaderProto.`readFrameFromHDFS(String fname, Types.ValueType[] schema, String[] names, long rlen, long clen)`
`FrameBlock` FrameReaderBinaryBlock.`readFrameFromHDFS(String fname, Types.ValueType[] schema, String[] names, long rlen, long clen)`
`FrameBlock` FrameReader.`readFrameFromInputStream(InputStream is, Types.ValueType[] schema, long rlen, long clen)`
`FrameBlock` FrameReaderTextCell.`readFrameFromInputStream(InputStream is, Types.ValueType[] schema, String[] names, long rlen, long clen)`
`abstract FrameBlock` FrameReader.`readFrameFromInputStream(InputStream is, Types.ValueType[] schema, String[] names, long rlen, long clen)`
`FrameBlock` FrameReaderTextCSV.`readFrameFromInputStream(InputStream is, Types.ValueType[] schema, String[] names, long rlen, long clen)`
`FrameBlock` FrameReaderProto.`readFrameFromInputStream(InputStream is, Types.ValueType[] schema, String[] names, long rlen, long clen)`
`FrameBlock` FrameReaderBinaryBlock.`readFrameFromInputStream(InputStream is, Types.ValueType[] schema, String[] names, long rlen, long clen)`
`TensorBlock` TensorReaderBinaryBlock.`readTensorFromHDFS(String fname, long[] dims, int blen, Types.ValueType[] schema)`
`TensorBlock` TensorReaderTextCell.`readTensorFromHDFS(String fname, long[] dims, int blen, Types.ValueType[] schema)`
`abstract TensorBlock` TensorReader.`readTensorFromHDFS(String fname, long[] dims, int blen, Types.ValueType[] schema)`

### Uses of Types.ValueType in org.apache.sysds.runtime.matrix.data

Methods in org.apache.sysds.runtime.matrix.data that return Types.ValueType
`Types.ValueType[]` FrameBlock.`getSchema()` Returns the schema of the frame block.

Methods in org.apache.sysds.runtime.matrix.data with parameters of type Types.ValueType
`Iterator<Object[]>` FrameBlock.`getObjectRowIterator(Types.ValueType[] schema)` Get a row iterator over the frame where all fields are encoded as boxed objects according to the value types of the provided target schema.
`void` FrameBlock.`setSchema(Types.ValueType[] schema)` Sets the schema of the frame block.

Constructors in org.apache.sysds.runtime.matrix.data with parameters of type Types.ValueType
Constructor and Description
`FrameBlock(int ncols, Types.ValueType vt)`
`FrameBlock(Types.ValueType[] schema)`
`FrameBlock(Types.ValueType[] schema, String[] names)`
`FrameBlock(Types.ValueType[] schema, String[][] data)`
`FrameBlock(Types.ValueType[] schema, String[] names, String[][] data)`

### Uses of Types.ValueType in org.apache.sysds.runtime.transform.decode

Methods in org.apache.sysds.runtime.transform.decode that return Types.ValueType
`Types.ValueType[]` Decoder.`getSchema()`

Methods in org.apache.sysds.runtime.transform.decode with parameters of type Types.ValueType
`static Decoder` DecoderFactory.`createDecoder(String spec, String[] colnames, Types.ValueType[] schema, FrameBlock meta)`
`static Decoder` DecoderFactory.`createDecoder(String spec, String[] colnames, Types.ValueType[] schema, FrameBlock meta, int clen)`
`static Decoder` DecoderFactory.`createDecoder(String spec, String[] colnames, Types.ValueType[] schema, FrameBlock meta, int minCol, int maxCol)`
`static Decoder` DecoderFactory.`createDecoder(String spec, String[] colnames, Types.ValueType[] schema, FrameBlock meta, int clen, int minCol, int maxCol)`

### Uses of Types.ValueType in org.apache.sysds.runtime.transform.encode

Methods in org.apache.sysds.runtime.transform.encode with parameters of type Types.ValueType
`static MultiColumnEncoder` EncoderFactory.`createEncoder(String spec, String[] colnames, Types.ValueType[] schema, FrameBlock meta)`
`static MultiColumnEncoder` EncoderFactory.`createEncoder(String spec, String[] colnames, Types.ValueType[] schema, FrameBlock meta, int minCol, int maxCol)`
`static MultiColumnEncoder` EncoderFactory.`createEncoder(String spec, String[] colnames, Types.ValueType[] schema, int clen, FrameBlock meta)`

### Uses of Types.ValueType in org.apache.sysds.runtime.transform.tokenize

Methods in org.apache.sysds.runtime.transform.tokenize that return Types.ValueType
`Types.ValueType[]` TokenizerPost.`getOutSchema()`
`Types.ValueType[]` TokenizerPostCount.`getOutSchema()`
`Types.ValueType[]` TokenizerPostPosition.`getOutSchema()`
`Types.ValueType[]` TokenizerPostHash.`getOutSchema()`
`Types.ValueType[]` Tokenizer.`getSchema()`

### Uses of Types.ValueType in org.apache.sysds.runtime.util

Methods in org.apache.sysds.runtime.util that return Types.ValueType
`static Types.ValueType[]` UtilFunctions.`copyOf(Types.ValueType[] schema1, Types.ValueType[] schema2)`
`static Types.ValueType[]` UtilFunctions.`nCopies(int n, Types.ValueType vt)`
`static Types.ValueType[]` UtilFunctions.`stringToValueType(String[] schemaValues)` Generates a ValueType array from a String array

Methods in org.apache.sysds.runtime.util with parameters of type Types.ValueType
`static int` UtilFunctions.`compareTo(Types.ValueType vt, Object in1, Object in2)`
`static MatrixBlock` Py4jConverterUtils.`convertPy4JArrayToMB(byte[] data, int rlen, int clen, boolean isSparse, Types.ValueType valueType)`
`static MatrixBlock` Py4jConverterUtils.`convertPy4JArrayToMB(byte[] data, int rlen, int clen, Types.ValueType valueType)`
`static FrameBlock` DataConverter.`convertToFrameBlock(MatrixBlock mb, Types.ValueType vt)` Converts a matrix block into a frame block of a given value type.
`static FrameBlock` DataConverter.`convertToFrameBlock(MatrixBlock mb, Types.ValueType[] schema)`
`static FrameBlock` DataConverter.`convertToFrameBlock(String[][] data, Types.ValueType[] schema)`
`static FrameBlock` DataConverter.`convertToFrameBlock(String[][] data, Types.ValueType[] schema, String[] colnames)`
`static TensorBlock` DataConverter.`convertToTensorBlock(MatrixBlock mb, Types.ValueType vt, boolean toBasicTensor)`
`static Types.ValueType[]` UtilFunctions.`copyOf(Types.ValueType[] schema1, Types.ValueType[] schema2)`
`static Types.ValueType[]` UtilFunctions.`copyOf(Types.ValueType[] schema1, Types.ValueType[] schema2)`
`static Object` UtilFunctions.`doubleToObject(Types.ValueType vt, double in)`
`static Object` UtilFunctions.`doubleToObject(Types.ValueType vt, double in, boolean sparse)`
`static int` UtilFunctions.`frequency(Types.ValueType[] schema, Types.ValueType vt)`
`static int` UtilFunctions.`frequency(Types.ValueType[] schema, Types.ValueType vt)`
`static FrameBlock` UtilFunctions.`generateRandomFrameBlock(int rows, int cols, Types.ValueType[] schema, Random random)` Generates a random FrameBlock with given parameters.
`static Object` UtilFunctions.`generateRandomValueFromValueType(Types.ValueType valueType, Random random)` Generates a random value for a given Value Type
`static String` HDFSTool.`metaDataToString(Types.ValueType vt, Types.ValueType[] schema, Types.DataType dt, DataCharacteristics dc, Types.FileFormat fmt, FileFormatProperties formatProperties, PrivacyConstraint privacyConstraint)`
`static String` HDFSTool.`metaDataToString(Types.ValueType vt, Types.ValueType[] schema, Types.DataType dt, DataCharacteristics dc, Types.FileFormat fmt, FileFormatProperties formatProperties, PrivacyConstraint privacyConstraint)`
`static Types.ValueType[]` UtilFunctions.`nCopies(int n, Types.ValueType vt)`
`static double` UtilFunctions.`objectToDouble(Types.ValueType vt, Object in)`
`static Object` UtilFunctions.`objectToObject(Types.ValueType vt, Object in)`
`static Object` UtilFunctions.`objectToObject(Types.ValueType vt, Object in, boolean ignoreNull)`
`static Object` HDFSTool.`readObjectFromHDFSFile(String filename, Types.ValueType vt)`
`static ScalarObject` HDFSTool.`readScalarObjectFromHDFSFile(String fname, Types.ValueType vt)`
`static TensorBlock` DataConverter.`readTensorFromHDFS(String dir, Types.FileFormat fmt, long[] dims, int blen, Types.ValueType[] schema)`
`static Object` UtilFunctions.`stringToObject(Types.ValueType vt, String in)`
`static void` HDFSTool.`writeMetaDataFile(String mtdfile, Types.ValueType vt, DataCharacteristics mc, Types.FileFormat fmt)`
`static void` HDFSTool.`writeMetaDataFile(String mtdfile, Types.ValueType vt, DataCharacteristics dc, Types.FileFormat fmt, FileFormatProperties formatProperties)`
`static void` HDFSTool.`writeMetaDataFile(String mtdfile, Types.ValueType vt, DataCharacteristics dc, Types.FileFormat fmt, FileFormatProperties formatProperties, PrivacyConstraint privacyConstraint)`
`static void` HDFSTool.`writeMetaDataFile(String mtdfile, Types.ValueType vt, DataCharacteristics mc, Types.FileFormat fmt, PrivacyConstraint privacyConstraint)`
`static void` HDFSTool.`writeMetaDataFile(String mtdfile, Types.ValueType vt, Types.ValueType[] schema, Types.DataType dt, DataCharacteristics mc, Types.FileFormat fmt)`
`static void` HDFSTool.`writeMetaDataFile(String mtdfile, Types.ValueType vt, Types.ValueType[] schema, Types.DataType dt, DataCharacteristics mc, Types.FileFormat fmt)`
`static void` HDFSTool.`writeMetaDataFile(String mtdfile, Types.ValueType vt, Types.ValueType[] schema, Types.DataType dt, DataCharacteristics dc, Types.FileFormat fmt, FileFormatProperties formatProperties)`
`static void` HDFSTool.`writeMetaDataFile(String mtdfile, Types.ValueType vt, Types.ValueType[] schema, Types.DataType dt, DataCharacteristics dc, Types.FileFormat fmt, FileFormatProperties formatProperties)`
`static void` HDFSTool.`writeMetaDataFile(String mtdfile, Types.ValueType vt, Types.ValueType[] schema, Types.DataType dt, DataCharacteristics dc, Types.FileFormat fmt, FileFormatProperties formatProperties, PrivacyConstraint privacyConstraint)`
`static void` HDFSTool.`writeMetaDataFile(String mtdfile, Types.ValueType vt, Types.ValueType[] schema, Types.DataType dt, DataCharacteristics dc, Types.FileFormat fmt, FileFormatProperties formatProperties, PrivacyConstraint privacyConstraint)`
`static void` HDFSTool.`writeMetaDataFile(String mtdfile, Types.ValueType vt, Types.ValueType[] schema, Types.DataType dt, DataCharacteristics mc, Types.FileFormat fmt, PrivacyConstraint privacyConstraint)`
`static void` HDFSTool.`writeMetaDataFile(String mtdfile, Types.ValueType vt, Types.ValueType[] schema, Types.DataType dt, DataCharacteristics mc, Types.FileFormat fmt, PrivacyConstraint privacyConstraint)`
`static void` HDFSTool.`writeScalarMetaDataFile(String mtdfile, Types.ValueType vt)`
`static void` HDFSTool.`writeScalarMetaDataFile(String mtdfile, Types.ValueType vt, PrivacyConstraint privacyConstraint)`