java.lang.Object
- org.apache.sysds.runtime.data.SparseBlock

All Implemented Interfaces:

Serializable, Block

Direct Known Subclasses:

SparseBlockCOO, SparseBlockCSR, SparseBlockDCSR, SparseBlockMCSR
```
public abstract class SparseBlock
extends Object
implements Serializable, Block
```
This SparseBlock is an abstraction for different sparse matrix formats. Since the design is a tradeoff between performance and generality, we restrict this abstraction to row-major sparse representations for now. All sparse matrix block operations are supposed to be implemented against this abstraction in order to enable variability/extensibility. Example sparse format that can be implemented efficiently include CSR, MCSR, and - with performance drawbacks - COO.

See Also:

Serialized Form

Nested Class Summary

Nested Classes
Modifier and Type Class Description

static class SparseBlock.Type

Constructor Summary

Constructors
Constructor Description

SparseBlock()

Method Summary

All Methods Instance Methods Abstract Methods Concrete Methods
Modifier and Type	Method	Description
`abstract boolean`	`add(int r, int c, double v)`	Add a value to a matrix cell (r,c).
`abstract void`	`allocate(int r)`	Allocate the underlying data structure holding non-zero values of row r if necessary.
`abstract void`	`allocate(int r, int nnz)`	Allocate the underlying data structure holding non-zero values of row r if necessary, w/ given size.
`abstract void`	`allocate(int r, int ennz, int maxnnz)`	Allocate the underlying data structure holding non-zero values of row r w/ the specified estimated nnz and max nnz.
`abstract void`	`append(int r, int c, double v)`	Append a value to the end of the physical representation.
`abstract boolean`	`checkValidity(int rlen, int clen, long nnz, boolean strict)`	Validate the correctness of the internal data structures of the different sparse block implementations.
`abstract void`	`compact(int r)`	Re-allocate physical row if physical size exceeds logical size plus resize factor.
`boolean`	`contains(double pattern)`	Checks if the block contains at least one value of the given pattern.
`List<Integer>`	`contains(double[] pattern, boolean earlyAbort)`
`abstract void`	`deleteIndexRange(int r, int cl, int cu)`	Deletes all non-zero values of the given column range [cl,cu) in row r.
`boolean`	`equals(double[] denseValues, int nCol)`	Get if the dense double array is equivalent to this sparse Block.
`boolean`	`equals(double[] denseValues, int nCol, double eps)`	Get if the dense double array is equivalent to this sparse Block.
`boolean`	`equals(Object o)`
`boolean`	`equals(SparseBlock o, double eps)`	Verify if the values in this sparse block is equivalent to that sparse block, not taking into account the dimensions of the contained values.
`abstract SparseRow`	`get(int r)`	Get values of row r in the format of a sparse row.
`abstract double`	`get(int r, int c)`	Get value of matrix cell (r,c).
`Iterator<IJV>`	`getIterator()`	Get a non-zero iterator over the entire sparse block.
`Iterator<IJV>`	`getIterator(int ru)`	Get a non-zero iterator over the partial sparse block [0,ru).
`Iterator<IJV>`	`getIterator(int rl, int ru)`	Get a non-zero iterator over the subblock [rl, ru).
`abstract int[]`	`indexes(int r)`	Get the sorted array of column indexes of all non-zero entries in row r.
`boolean`	`isAligned(int r, SparseBlock that)`	Indicates if all non-zero values of row r are aligned with the same row of the given second sparse block instance, which can be exploited for more efficient operations.
`boolean`	`isAligned(SparseBlock that)`	Indicates if all non-zero values are aligned with the given second sparse block instance, which can be exploited for more efficient operations.
`abstract boolean`	`isAllocated(int r)`	Indicates if the underlying data structure for a given row is already allocated.
`abstract boolean`	`isContiguous()`	Indicates if the underlying data structures returned by values and indexes are contiguous arrays, which can be exploited for more efficient operations.
`abstract boolean`	`isEmpty(int r)`	Get information if row r is empty, i.e., does not contain non-zero values.
`abstract boolean`	`isThreadSafe()`	Indicates if the underlying implementation allows thread-safe row updates if concurrent threads update disjoint rows.
`abstract int`	`numRows()`	Get the number of rows in the sparse block.
`abstract int`	`pos(int r)`	Get the starting position of row r in the indexes/values arrays returned by indexes(r) and values(r).
`abstract int`	`posFIndexGT(int r, int c)`	Get position of first column index greater than column c in row r.
`abstract int`	`posFIndexGTE(int r, int c)`	Get position of first column index greater than or equal column c in row r.
`abstract int`	`posFIndexLTE(int r, int c)`	Get position of first column index lower than or equal column c in row r.
`abstract void`	`reset()`	Clears the sparse block by deleting non-zero values.
`abstract void`	`reset(int ennz, int maxnnz)`	Clears the sparse block by deleting non-zero values.
`abstract void`	`reset(int r, int ennz, int maxnnz)`	Clears row r of the sparse block by deleting non-zero values.
`abstract boolean`	`set(int r, int c, double v)`	Set the value of a matrix cell (r,c).
`abstract void`	`set(int r, SparseRow row, boolean deep)`	Set the values of row r to the given sparse row.
`abstract void`	`setIndexRange(int r, int cl, int cu, double[] v, int[] vix, int vpos, int vlen)`	Sets a sparse array of non-zeros values and indexes into the column range [cl,cu) in row r.
`abstract void`	`setIndexRange(int r, int cl, int cu, double[] v, int vix, int vlen)`	Sets a dense array of non-zeros values into the column range [cl,cu) in row r.
`abstract long`	`size()`	Get the number of non-zero values in the sparse block.
`abstract int`	`size(int r)`	Get the number of non-zero values in row r.
`abstract long`	`size(int rl, int ru)`	Get the number of non-zeros values in the row range of [rl, ru).
`abstract long`	`size(int rl, int ru, int cl, int cu)`	Get the number of non-zeros values in the row and column range of [rl/cl, ru/cu);
`abstract void`	`sort()`	Sort all non-zero value/index pairs of the sparse block by row and column index.
`abstract void`	`sort(int r)`	Sort all non-zero value/index pairs of row r column index.
`abstract String`	`toString()`
`abstract double[]`	`values(int r)`	Get the array of all non-zero entries in row r, sorted by their column indexes.

Methods inherited from class java.lang.Object
getClass, hashCode, notify, notifyAll, wait, wait, wait

- Constructor Detail
  - SparseBlock
```
public SparseBlock()
```
- Method Detail
  - allocate
```
public abstract void allocate(int r)
```
    Allocate the underlying data structure holding non-zero values of row r if necessary.
    
    Parameters:
    
    r - row index
  - allocate
```
public abstract void allocate(int r,
                              int nnz)
```
    Allocate the underlying data structure holding non-zero values of row r if necessary, w/ given size.
    
    Parameters:
    
    r - row index
    
    nnz - number of non-zeros
  - allocate
```
public abstract void allocate(int r,
                              int ennz,
                              int maxnnz)
```
    Allocate the underlying data structure holding non-zero values of row r w/ the specified estimated nnz and max nnz.
    
    Parameters:
    
    r - row index
    
    ennz - estimated non-zeros
    
    maxnnz - max non-zeros
  - compact
```
public abstract void compact(int r)
```
    Re-allocate physical row if physical size exceeds logical size plus resize factor.
    
    Parameters:
    
    r - row index
  - numRows
```
public abstract int numRows()
```
    Get the number of rows in the sparse block.
    
    Returns:
    
    number of rows
  - isThreadSafe
```
public abstract boolean isThreadSafe()
```
    Indicates if the underlying implementation allows thread-safe row updates if concurrent threads update disjoint rows.
    
    Returns:
    
    true if thread-safe row updates
  - isContiguous
```
public abstract boolean isContiguous()
```
    Indicates if the underlying data structures returned by values and indexes are contiguous arrays, which can be exploited for more efficient operations.
    
    Returns:
    
    true if underlying data structures are contiguous arrays
  - isAligned
```
public boolean isAligned(SparseBlock that)
```
    Indicates if all non-zero values are aligned with the given second sparse block instance, which can be exploited for more efficient operations. Two non-zeros are aligned if they have the same column index and reside in the same array position.
    
    Parameters:
    
    that - sparse block
    
    Returns:
    
    true if all non-zero values are aligned with the given second sparse block
  - isAligned
```
public boolean isAligned(int r,
                         SparseBlock that)
```
    Indicates if all non-zero values of row r are aligned with the same row of the given second sparse block instance, which can be exploited for more efficient operations. Two non-zeros are aligned if they have the same column index and reside in the same array position.
    
    Parameters:
    
    r - row index starting at 0
    
    that - sparse block
    
    Returns:
    
    true if all non-zero values of row r are aligned with the same row of the given second sparse block instance
  - isAllocated
```
public abstract boolean isAllocated(int r)
```
    Indicates if the underlying data structure for a given row is already allocated.
    
    Parameters:
    
    r - row index
    
    Returns:
    
    true if already allocated
  - reset
```
public abstract void reset()
```
    Clears the sparse block by deleting non-zero values. After this call all size() calls are guaranteed to return 0.
  - reset
```
public abstract void reset(int ennz,
                           int maxnnz)
```
    Clears the sparse block by deleting non-zero values. After this call all size() calls are guaranteed to return 0.
    
    Parameters:
    
    ennz - estimated non-zeros
    
    maxnnz - max non-zeros
  - reset
```
public abstract void reset(int r,
                           int ennz,
                           int maxnnz)
```
    Clears row r of the sparse block by deleting non-zero values. After this call size(r) is guaranteed to return 0.
    
    Parameters:
    
    r - row index
    
    ennz - estimated non-zeros
    
    maxnnz - max non-zeros
  - size
```
public abstract long size()
```
    Get the number of non-zero values in the sparse block.
    
    Returns:
    
    number of non-zero values in sparse block
  - size
```
public abstract int size(int r)
```
    Get the number of non-zero values in row r.
    
    Parameters:
    
    r - row index starting at 0
    
    Returns:
    
    number of non-zero values in row r
  - size
```
public abstract long size(int rl,
                          int ru)
```
    Get the number of non-zeros values in the row range of [rl, ru).
    
    Parameters:
    
    rl - row lower index
    
    ru - row upper index
    
    Returns:
    
    number of non-zero values in the row range
  - size
```
public abstract long size(int rl,
                          int ru,
                          int cl,
                          int cu)
```
    Get the number of non-zeros values in the row and column range of [rl/cl, ru/cu);
    
    Parameters:
    
    rl - row lower index
    
    ru - row upper index
    
    cl - column lower index
    
    cu - column upper index
    
    Returns:
    
    number of non-zero values in the row and column range
  - isEmpty
```
public abstract boolean isEmpty(int r)
```
    Get information if row r is empty, i.e., does not contain non-zero values. Equivalent to size(r)==0. Users should do this check if it is unknown if the underlying row data structure is allocated.
    
    Parameters:
    
    r - row index starting at 0
    
    Returns:
    
    true if row does not contain non-zero values
  - checkValidity
```
public abstract boolean checkValidity(int rlen,
                                      int clen,
                                      long nnz,
                                      boolean strict)
```
    Validate the correctness of the internal data structures of the different sparse block implementations.
    
    Parameters:
    
    rlen - number of rows
    
    clen - number of columns
    
    nnz - number of non zeros
    
    strict - enforce optional properties
    
    Returns:
    
    true if the sparse block is valid wrt the corresponding format such as COO, CSR, MCSR.
  - indexes
```
public abstract int[] indexes(int r)
```
    Get the sorted array of column indexes of all non-zero entries in row r. Note that - for flexibility of the implementing format - the returned array may be larger, where the range for row r is given by [pos(r),pos(r)+size(r)).
    
    Parameters:
    
    r - row index starting at 0
    
    Returns:
    
    sorted array of column indexes
  - values
```
public abstract double[] values(int r)
```
    Get the array of all non-zero entries in row r, sorted by their column indexes. Note that - for flexibility of the implementing format - the returned array may be larger, where the range for row r is given by [pos(r),pos(r)+size(r)).
    
    Parameters:
    
    r - row index starting at 0
    
    Returns:
    
    array of all non-zero entries in row r sorted by column indexes
  - pos
```
public abstract int pos(int r)
```
    Get the starting position of row r in the indexes/values arrays returned by indexes(r) and values(r).
    
    Parameters:
    
    r - row index starting at 0
    
    Returns:
    
    starting position of row r
  - set
```
public abstract boolean set(int r,
                            int c,
                            double v)
```
    Set the value of a matrix cell (r,c). This might update an existing non-zero value, insert a new non-zero value, or delete a non-zero value.
    
    Parameters:
    
    r - row index starting at 0
    
    c - column index starting at 0
    
    v - zero or non-zero value
    
    Returns:
    
    true, if number of non-zeros changed
  - set
```
public abstract void set(int r,
                         SparseRow row,
                         boolean deep)
```
    Set the values of row r to the given sparse row. This might update existing non-zero values, insert a new row, or delete a row. NOTE: This method exists for incremental runtime integration and might be deleted in the future.
    
    Parameters:
    
    r - row index starting at 0
    
    row - sparse row
    
    deep - indicator to create deep copy of sparse row
  - add
```
public abstract boolean add(int r,
                            int c,
                            double v)
```
    Add a value to a matrix cell (r,c). This might update an existing non-zero value, or insert a new non-zero value.
    
    Parameters:
    
    r - row index starting at 0
    
    c - column index starting at 0
    
    v - zero or non-zero value
    
    Returns:
    
    true, if number of non-zeros changed
  - append
```
public abstract void append(int r,
                            int c,
                            double v)
```
    Append a value to the end of the physical representation. This should only be used for operations with sequential write pattern or if followed by a sort() operation. Note that this operation does not perform any matrix cell updates.
    
    Parameters:
    
    r - row index starting at 0
    
    c - column index starting at 0
    
    v - zero or non-zero value
  - setIndexRange
```
public abstract void setIndexRange(int r,
                                   int cl,
                                   int cu,
                                   double[] v,
                                   int vix,
                                   int vlen)
```
    Sets a dense array of non-zeros values into the column range [cl,cu) in row r. The passed value array may be larger and the relevant range is given by [vix,vix+len).
    
    Parameters:
    
    r - row index starting at 0
    
    cl - lower column index starting at 0
    
    cu - upper column index starting at 0
    
    v - value array
    
    vix - start index in value array
    
    vlen - number of relevant values
  - setIndexRange
```
public abstract void setIndexRange(int r,
                                   int cl,
                                   int cu,
                                   double[] v,
                                   int[] vix,
                                   int vpos,
                                   int vlen)
```
    Sets a sparse array of non-zeros values and indexes into the column range [cl,cu) in row r. The passed value array may be larger.
    
    Parameters:
    
    r - row index starting at 0
    
    cl - lower column index starting at 0
    
    cu - upper column index starting at 0
    
    v - value array
    
    vix - column index array
    
    vpos - start index in value and index arrays
    
    vlen - number of relevant values
  - deleteIndexRange
```
public abstract void deleteIndexRange(int r,
                                      int cl,
                                      int cu)
```
    Deletes all non-zero values of the given column range [cl,cu) in row r.
    
    Parameters:
    
    r - row index starting at 0
    
    cl - lower column index starting at 0
    
    cu - upper column index starting at 0
  - sort
```
public abstract void sort()
```
    Sort all non-zero value/index pairs of the sparse block by row and column index.
  - sort
```
public abstract void sort(int r)
```
    Sort all non-zero value/index pairs of row r column index.
    
    Parameters:
    
    r - row index starting at 0
  - get
```
public abstract double get(int r,
                           int c)
```
    Get value of matrix cell (r,c). In case of non existing values this call returns 0.
    
    Specified by:
    
    get in interface Block
    
    Parameters:
    
    r - row index starting at 0
    
    c - column index starting at 0
    
    Returns:
    
    value of cell at position (r,c)
  - get
```
public abstract SparseRow get(int r)
```
    Get values of row r in the format of a sparse row.
    
    Parameters:
    
    r - row index starting at 0
    
    Returns:
    
    values of row r as a sparse row
  - posFIndexLTE
```
public abstract int posFIndexLTE(int r,
                                 int c)
```
    Get position of first column index lower than or equal column c in row r. The position is relative to the indexes/values arrays returned by indexes(r) and values(r). If no such value exists, this call returns -1.
    
    Parameters:
    
    r - row index starting at 0
    
    c - column index starting at 0
    
    Returns:
    
    position of the first column index lower than or equal to column c in row r
  - posFIndexGTE
```
public abstract int posFIndexGTE(int r,
                                 int c)
```
    Get position of first column index greater than or equal column c in row r. The position is relative to the indexes/values arrays returned by indexes(r) and values(r). If no such value exists, this call returns -1. Note if CSR the pos(r) is subtracted from the result.
    
    Parameters:
    
    r - row index starting at 0
    
    c - column index starting at 0
    
    Returns:
    
    position of the first column index greater than or equal to column c in row r
  - posFIndexGT
```
public abstract int posFIndexGT(int r,
                                int c)
```
    Get position of first column index greater than column c in row r. The position is relative to the indexes/values arrays returned by indexes(r) and values(r). If no such value exists, this call returns -1.
    
    Parameters:
    
    r - row index starting at 0
    
    c - column index starting at 0
    
    Returns:
    
    position of the first column index greater than column c in row r
  - contains
```
public boolean contains(double pattern)
```
    Checks if the block contains at least one value of the given pattern. Implementations need to handle NaN patterns as well (note that NaN==NaN yields false).
    
    Parameters:
    
    pattern - checked pattern
    
    Returns:
    
    true if pattern appears at least once, otherwise false
  - contains
```
public List<Integer> contains(double[] pattern,
                              boolean earlyAbort)
```
  - getIterator
```
public Iterator<IJV> getIterator()
```
    Get a non-zero iterator over the entire sparse block. Note that the returned IJV object is reused across next calls and should be directly consumed or deep copied.
    
    Returns:
    
    IJV iterator
  - getIterator
```
public Iterator<IJV> getIterator(int ru)
```
    Get a non-zero iterator over the partial sparse block [0,ru). Note that the returned IJV object is reused across next calls and should be directly consumed or deep copied.
    
    Parameters:
    
    ru - exclusive upper row index starting at 0
    
    Returns:
    
    IJV iterator
  - getIterator
```
public Iterator<IJV> getIterator(int rl,
                                 int ru)
```
    Get a non-zero iterator over the subblock [rl, ru). Note that the returned IJV object is reused across next calls and should be directly consumed or deep copied.
    
    Parameters:
    
    rl - inclusive lower row index starting at 0
    
    ru - exclusive upper row index starting at 0
    
    Returns:
    
    IJV iterator
  - toString
```
public abstract String toString()
```
    Overrides:
    
    toString in class Object
  - equals
```
public boolean equals(Object o)
```
    Overrides:
    
    equals in class Object
  - equals
```
public boolean equals(SparseBlock o,
                      double eps)
```
    Verify if the values in this sparse block is equivalent to that sparse block, not taking into account the dimensions of the contained values.
    
    Parameters:
    
    o - Other block
    
    eps - Epsilon allowed
    
    Returns:
    
    If the blocs are equivalent.
  - equals
```
public boolean equals(double[] denseValues,
                      int nCol)
```
    Get if the dense double array is equivalent to this sparse Block.
    
    Parameters:
    
    denseValues - row major double values same dimensions of sparse Block.
    
    nCol - Number of columns in dense values (and hopefully in this sparse block)
    
    Returns:
    
    If the dense array is equivalent
  - equals
```
public boolean equals(double[] denseValues,
                      int nCol,
                      double eps)
```
    Get if the dense double array is equivalent to this sparse Block.
    
    Parameters:
    
    denseValues - row major double values same dimensions of sparse Block.
    
    nCol - Number of columns in dense values (and hopefully in this sparse block)
    
    eps - Epsilon allowed to be off. Note we treat zero differently and it must be zero.
    
    Returns:
    
    If the dense array is equivalent

Class SparseBlock

Nested Class Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

SparseBlock

Method Detail

allocate

allocate

allocate

compact

numRows

isThreadSafe

isContiguous

isAligned

isAligned

isAllocated

reset

reset

reset

size

size

size

size

isEmpty

checkValidity

indexes

values

pos

set

set

add

append

setIndexRange

setIndexRange

deleteIndexRange

sort

sort

get

get

posFIndexLTE

posFIndexGTE

posFIndexGT

contains

contains

getIterator

getIterator

getIterator

toString

equals

equals

equals

equals