Package org.apache.sysds.runtime.transform.encode

Class LegacyEncoder

java.lang.Object

org.apache.sysds.runtime.transform.encode.LegacyEncoder

All Implemented Interfaces:

Externalizable, Serializable

Direct Known Subclasses:

EncoderMVImpute, EncoderOmit

public abstract class LegacyEncoder
extends Object
implements Externalizable

Base class for all transform encoders providing both a row and block interface for decoding frames to matrices.

See Also:

Serialized Form

Method Summary

Modifier and Type	Method	Description
abstract MatrixBlock	apply(FrameBlock in, MatrixBlock out)	Encode input data blockwise according to existing transform meta data (transform apply).
abstract void	build(FrameBlock in)	Build the transform meta data for the given block input.
void	buildPartial(FrameBlock in)	Partial build of internal data structures (e.g., in distributed spark operations).
abstract MatrixBlock	encode(FrameBlock in, MatrixBlock out)	Block encode: build and apply (transform encode).
int[]	getColList()
MatrixBlock	getColMapping(FrameBlock meta, MatrixBlock out)	Obtain the column mapping of encoded frames based on the passed meta data frame.
abstract FrameBlock	getMetaData(FrameBlock out)	Construct a frame block out of the transform meta data.
int	initColList(int[] colList)
int	initColList(org.apache.wink.json4j.JSONArray attrs)
abstract void	initMetaData(FrameBlock meta)	Sets up the required meta data for a subsequent call to apply.
boolean	isApplicable()	Indicates if this encoder is applicable, i.e, if there is at least one column to encode.
int	isApplicable(int colID)	Indicates if this encoder is applicable for the given column ID, i.e., if it is subject to this transformation.
void	mergeAt(LegacyEncoder other, int row, int col)	Merges another encoder, of a compatible type, in after a certain position.
void	prepareBuildPartial()	Allocates internal data structures for partial build.
void	readExternal(ObjectInput in)	Redirects the default java serialization via externalizable to our default hadoop writable serialization for efficient broadcast/rdd deserialization.
void	setColList(int[] colList)
void	shiftCols(int offset)
LegacyEncoder	subRangeEncoder(IndexRange ixRange)	Returns a new Encoder that only handles a sub range of columns.
void	updateIndexRanges(long[] beginDims, long[] endDims)	Update index-ranges to after encoding.
void	writeExternal(ObjectOutput os)	Redirects the default java serialization via externalizable to our default hadoop writable serialization for efficient broadcast/rdd serialization.

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Detail

getColList

public int[] getColList()

setColList

public void setColList(int[] colList)

initColList

public int initColList(org.apache.wink.json4j.JSONArray attrs)

initColList

public int initColList(int[] colList)

isApplicable

public boolean isApplicable()

Indicates if this encoder is applicable, i.e, if there is at least one column to encode.

Returns:

true if at least one column to encode

isApplicable

public int isApplicable(int colID)

Indicates if this encoder is applicable for the given column ID, i.e., if it is subject to this transformation.

Parameters:

colID - column ID

Returns:

true if encoder is applicable for given column

encode

public abstract MatrixBlock encode(FrameBlock in,
                                   MatrixBlock out)

Block encode: build and apply (transform encode).

Parameters:

in - input frame block

out - output matrix block

Returns:

output matrix block

build

public abstract void build(FrameBlock in)

Build the transform meta data for the given block input. This call modifies and keeps meta data as encoder state.

Parameters:

in - input frame block

prepareBuildPartial

public void prepareBuildPartial()

Allocates internal data structures for partial build.

buildPartial

public void buildPartial(FrameBlock in)

Partial build of internal data structures (e.g., in distributed spark operations).

Parameters:

in - input frame block

apply

public abstract MatrixBlock apply(FrameBlock in,
                                  MatrixBlock out)

Encode input data blockwise according to existing transform meta data (transform apply).

Parameters:

in - input frame block

out - output matrix block

Returns:

output matrix block

subRangeEncoder

public LegacyEncoder subRangeEncoder(IndexRange ixRange)

Returns a new Encoder that only handles a sub range of columns.

Parameters:

ixRange - the range (1-based, begin inclusive, end exclusive)

Returns:

an encoder of the same type, just for the sub-range

mergeAt

public void mergeAt(LegacyEncoder other,
                    int row,
                    int col)

Merges another encoder, of a compatible type, in after a certain position. Resizes as necessary. Encoders are compatible with themselves and EncoderComposite is compatible with every other Encoder.

Parameters:

other - the encoder that should be merged in

row - the row where it should be placed (1-based)

col - the col where it should be placed (1-based)

updateIndexRanges

public void updateIndexRanges(long[] beginDims,
                              long[] endDims)

Update index-ranges to after encoding. Note that only Dummycoding changes the ranges.

Parameters:

beginDims - begin dimensions of range

endDims - end dimensions of range

getMetaData

public abstract FrameBlock getMetaData(FrameBlock out)

Construct a frame block out of the transform meta data.

Parameters:

out - output frame block

Returns:

output frame block?

initMetaData

public abstract void initMetaData(FrameBlock meta)

Sets up the required meta data for a subsequent call to apply.

Parameters:

meta - frame block

getColMapping

public MatrixBlock getColMapping(FrameBlock meta,
                                 MatrixBlock out)

Obtain the column mapping of encoded frames based on the passed meta data frame.

Parameters:

meta - meta data frame block

out - output matrix

Returns:

matrix with column mapping (one row per attribute)

writeExternal

public void writeExternal(ObjectOutput os)
                   throws IOException

Redirects the default java serialization via externalizable to our default hadoop writable serialization for efficient broadcast/rdd serialization.

Specified by:

writeExternal in interface Externalizable

Parameters:

os - object output

Throws:

IOException - if IOException occurs

readExternal

public void readExternal(ObjectInput in)
                  throws IOException

Redirects the default java serialization via externalizable to our default hadoop writable serialization for efficient broadcast/rdd deserialization.

Specified by:

readExternal in interface Externalizable

Parameters:

in - object input

Throws:

IOException - if IOException occur

shiftCols

public void shiftCols(int offset)