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Introduce kudo serialization format. #2532

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23 changes: 23 additions & 0 deletions src/main/java/com/nvidia/spark/rapids/jni/Pair.java
Original file line number Diff line number Diff line change
@@ -0,0 +1,23 @@
package com.nvidia.spark.rapids.jni;

public class Pair<K, V> {
private final K left;
private final V right;

public Pair(K left, V right) {
this.left = left;
this.right = right;
}

public K getLeft() {
return left;
}

public V getRight() {
return right;
}

public static <K, V> Pair<K, V> of(K left, V right) {
return new Pair<>(left, right);
}
}
49 changes: 49 additions & 0 deletions src/main/java/com/nvidia/spark/rapids/jni/SlicedTable.java
Original file line number Diff line number Diff line change
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package com.nvidia.spark.rapids.jni;

import ai.rapids.cudf.Table;

import java.util.Objects;

import static com.nvidia.spark.rapids.jni.TableUtils.ensure;


/**
* A sliced view to table.
* This table doesn't change ownership of the underlying data.
*/
public class SlicedTable {
private final long startRow;
private final long numRows;
private final Table table;

public SlicedTable(long startRow, long numRows, Table table) {
Objects.requireNonNull(table, "table must not be null");
ensure(startRow >= 0, "startRow must be >= 0");
ensure(startRow < table.getRowCount(),
() -> "startRow " + startRow + " is larger than table row count " + table.getRowCount());
ensure(numRows >= 0, () -> "numRows " + numRows + " is negative");
ensure(startRow + numRows <= table.getRowCount(), () -> "startRow + numRows is " + (startRow + numRows)
+ ", must be less than table row count " + table.getRowCount());

this.startRow = startRow;
this.numRows = numRows;
this.table = table;
}

public long getStartRow() {
return startRow;
}

public long getNumRows() {
return numRows;
}

public Table getTable() {
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This might be better named getUnslicedTable or getBaseTable as its name implies it could manifest the table after slicing takes effect.

There needs to be documentation for this method re: ownership expectations of the result, i.e.: is the caller responsible for closing the table? If so, this should arguably invalidate the local table here. If not, who ultimately should close it?

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Will fix it.

return table;
}

public static SlicedTable from(Table table, long startRow, long numRows) {
return new SlicedTable(startRow, numRows, table);
}
}

73 changes: 73 additions & 0 deletions src/main/java/com/nvidia/spark/rapids/jni/TableUtils.java
Original file line number Diff line number Diff line change
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package com.nvidia.spark.rapids.jni;

import java.util.Arrays;
import java.util.Iterator;
import java.util.function.Function;
import java.util.function.LongConsumer;
import java.util.function.Supplier;
import java.util.stream.Collectors;

public class TableUtils {

public static void ensure(boolean condition, String message) {
if (!condition) {
throw new IllegalArgumentException(message);
}
}

public static void ensure(boolean condition, Supplier<String> messageSupplier) {
if (!condition) {
throw new IllegalArgumentException(messageSupplier.get());
}
}
Comment on lines +12 to +22
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Nit: These have nothing to do with Table, should be in an assertion, precondition, or more generic utility class. Similar comment for closeException, closeQuietly, and withTime.

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Will fix it.


/**
* This method returns the length in bytes needed to represent X number of rows
* e.g. getValidityLengthInBytes(5) => 1 byte
* getValidityLengthInBytes(7) => 1 byte
* getValidityLengthInBytes(14) => 2 bytes
*/
public static long getValidityLengthInBytes(long rows) {
return (rows + 7) / 8;
}

public static <R extends AutoCloseable, T> T closeIfException(R resource, Function<R, T> function) {
try {
return function.apply(resource);
} catch (Exception e) {
if (resource != null) {
try {
resource.close();
} catch (Exception inner) {
// ignore
}
}
throw e;
}
}

public static <R extends AutoCloseable> void closeQuietly(Iterator<R> resources) {
while (resources.hasNext()) {
try {
resources.next().close();
} catch (Exception e) {
// ignore
}
}
}

public static <R extends AutoCloseable> void closeQuietly(R... resources) {
closeQuietly(Arrays.stream(resources).collect(Collectors.toList()));
}

public static <R extends AutoCloseable> void closeQuietly(Iterable<R> resources) {
closeQuietly(resources.iterator());
}

public static <T> T withTime(Supplier<T> task, LongConsumer timeConsumer) {
long now = System.nanoTime();
T ret = task.get();
timeConsumer.accept(System.nanoTime() - now);
return ret;
}
}
Original file line number Diff line number Diff line change
@@ -0,0 +1,47 @@
package com.nvidia.spark.rapids.jni.kudo;

import java.util.OptionalLong;

/**
* This class is used to store the offsets of the buffer of a column in the serialized data.
*/
public class ColumnOffsetInfo {
private static final long INVALID_OFFSET = -1L;
private final long validity;
private final long offset;
private final long data;
private final long dataLen;

public ColumnOffsetInfo(long validity, long offset, long data, long dataLen) {
this.validity = validity;
this.offset = offset;
this.data = data;
this.dataLen = dataLen;
}

public OptionalLong getValidity() {
return (validity == INVALID_OFFSET) ? OptionalLong.empty() : OptionalLong.of(validity);
}

public OptionalLong getOffset() {
return (offset == INVALID_OFFSET) ? OptionalLong.empty() : OptionalLong.of(offset);
}

public OptionalLong getData() {
return (data == INVALID_OFFSET) ? OptionalLong.empty() : OptionalLong.of(data);
}

public long getDataLen() {
return dataLen;
}

@Override
public String toString() {
return "ColumnOffsets{" +
"validity=" + validity +
", offset=" + offset +
", data=" + data +
", dataLen=" + dataLen +
'}';
}
}
58 changes: 58 additions & 0 deletions src/main/java/com/nvidia/spark/rapids/jni/kudo/ColumnViewInfo.java
Original file line number Diff line number Diff line change
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package com.nvidia.spark.rapids.jni.kudo;

import ai.rapids.cudf.DType;
import ai.rapids.cudf.DeviceMemoryBuffer;

import static com.nvidia.spark.rapids.jni.kudo.KudoSerializer.safeLongToInt;


public class ColumnViewInfo {
private final DType dtype;
private final ColumnOffsetInfo offsetInfo;
private final long nullCount;
private final long rowCount;

public ColumnViewInfo(DType dtype, ColumnOffsetInfo offsetInfo,
long nullCount, long rowCount) {
this.dtype = dtype;
this.offsetInfo = offsetInfo;
this.nullCount = nullCount;
this.rowCount = rowCount;
}

public long buildColumnView(DeviceMemoryBuffer buffer, long[] childrenView) {
long bufferAddress = buffer.getAddress();

long dataAddress = 0;
if (offsetInfo.getData().isPresent()) {
dataAddress = buffer.getAddress() + offsetInfo.getData().getAsLong();
}

long validityAddress = 0;
if (offsetInfo.getValidity().isPresent()) {
validityAddress = offsetInfo.getValidity().getAsLong() + bufferAddress;
}

long offsetsAddress = 0;
if (offsetInfo.getOffset().isPresent()) {
offsetsAddress = offsetInfo.getOffset().getAsLong() + bufferAddress;
}

return RefUtils.makeCudfColumnView(
dtype.getTypeId().getNativeId(), dtype.getScale(),
dataAddress, offsetInfo.getDataLen(),
offsetsAddress, validityAddress,
safeLongToInt(nullCount), safeLongToInt(rowCount),
childrenView);
}

@Override
public String toString() {
return "ColumnViewInfo{" +
"dtype=" + dtype +
", offsetInfo=" + offsetInfo +
", nullCount=" + nullCount +
", rowCount=" + rowCount +
'}';
}
}
Original file line number Diff line number Diff line change
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package com.nvidia.spark.rapids.jni.kudo;

import ai.rapids.cudf.HostMemoryBuffer;

import java.io.DataOutputStream;
import java.io.IOException;

/**
* Visible for testing
*/
class DataOutputStreamWriter extends DataWriter {
private final byte[] arrayBuffer = new byte[1024 * 128];
private final DataOutputStream dout;

public DataOutputStreamWriter(DataOutputStream dout) {
this.dout = dout;
}

@Override
public void writeByte(byte b) throws IOException {
dout.writeByte(b);
}

@Override
public void writeShort(short s) throws IOException {
dout.writeShort(s);
}

@Override
public void writeInt(int i) throws IOException {
dout.writeInt(i);
}

@Override
public void writeIntNativeOrder(int i) throws IOException {
// TODO this only works on Little Endian Architectures, x86. If we need
// to support others we need to detect the endianness and switch on the right implementation.
writeInt(Integer.reverseBytes(i));
}

@Override
public void writeLong(long val) throws IOException {
dout.writeLong(val);
}

@Override
public void copyDataFrom(HostMemoryBuffer src, long srcOffset, long len) throws IOException {
long dataLeft = len;
while (dataLeft > 0) {
int amountToCopy = (int)Math.min(arrayBuffer.length, dataLeft);
src.getBytes(arrayBuffer, 0, srcOffset, amountToCopy);
dout.write(arrayBuffer, 0, amountToCopy);
srcOffset += amountToCopy;
dataLeft -= amountToCopy;
}
}

@Override
public void flush() throws IOException {
dout.flush();
}

@Override
public void write(byte[] arr, int offset, int length) throws IOException {
dout.write(arr, offset, length);
}
}
36 changes: 36 additions & 0 deletions src/main/java/com/nvidia/spark/rapids/jni/kudo/DataWriter.java
Original file line number Diff line number Diff line change
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package com.nvidia.spark.rapids.jni.kudo;

import ai.rapids.cudf.HostMemoryBuffer;

import java.io.IOException;

/**
* Visible for testing
*/
abstract class DataWriter {

public abstract void writeByte(byte b) throws IOException;

public abstract void writeShort(short s) throws IOException;

public abstract void writeInt(int i) throws IOException;

public abstract void writeIntNativeOrder(int i) throws IOException;

public abstract void writeLong(long val) throws IOException;

/**
* Copy data from src starting at srcOffset and going for len bytes.
*
* @param src where to copy from.
* @param srcOffset offset to start at.
* @param len amount to copy.
*/
public abstract void copyDataFrom(HostMemoryBuffer src, long srcOffset, long len) throws IOException;

public void flush() throws IOException {
// NOOP by default
}

public abstract void write(byte[] arr, int offset, int length) throws IOException;
}
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