HADOOP-12826. Rename the new Java coder and make it default. Contributed by Rui Li.
This commit is contained in:
Zhe Zhang
parent
1898810cda
commit
19e8f07691
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@ -20,7 +20,14 @@ package org.apache.hadoop.io.erasurecode;
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import org.apache.hadoop.classification.InterfaceAudience;
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import org.apache.hadoop.conf.Configuration;
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import org.apache.hadoop.fs.CommonConfigurationKeys;
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import org.apache.hadoop.io.erasurecode.rawcoder.*;
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import org.apache.hadoop.io.erasurecode.rawcoder.RSRawDecoder;
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import org.apache.hadoop.io.erasurecode.rawcoder.RSRawEncoder;
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import org.apache.hadoop.io.erasurecode.rawcoder.RawErasureCoder;
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import org.apache.hadoop.io.erasurecode.rawcoder.RawErasureCoderFactory;
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import org.apache.hadoop.io.erasurecode.rawcoder.RawErasureDecoder;
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import org.apache.hadoop.io.erasurecode.rawcoder.RawErasureEncoder;
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import org.apache.hadoop.io.erasurecode.rawcoder.XORRawDecoder;
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import org.apache.hadoop.io.erasurecode.rawcoder.XORRawEncoder;
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/**
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* A codec & coder utility to help create raw coders conveniently.
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@ -43,7 +50,7 @@ public final class CodecUtil {
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CommonConfigurationKeys.IO_ERASURECODE_CODEC_RS_RAWCODER_KEY,
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true, numDataUnits, numParityUnits);
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if (rawCoder == null) {
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rawCoder = new RSRawEncoderLegacy(numDataUnits, numParityUnits);
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rawCoder = new RSRawEncoder(numDataUnits, numParityUnits);
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}
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return (RawErasureEncoder) rawCoder;
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@ -62,7 +69,7 @@ public final class CodecUtil {
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CommonConfigurationKeys.IO_ERASURECODE_CODEC_RS_RAWCODER_KEY,
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false, numDataUnits, numParityUnits);
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if (rawCoder == null) {
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rawCoder = new RSRawDecoderLegacy(numDataUnits, numParityUnits);
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rawCoder = new RSRawDecoder(numDataUnits, numParityUnits);
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}
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return (RawErasureDecoder) rawCoder;
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@ -23,7 +23,6 @@ import org.apache.hadoop.io.erasurecode.rawcoder.util.CoderUtil;
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import org.apache.hadoop.io.erasurecode.rawcoder.util.DumpUtil;
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import org.apache.hadoop.io.erasurecode.rawcoder.util.GF256;
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import org.apache.hadoop.io.erasurecode.rawcoder.util.RSUtil;
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import org.apache.hadoop.io.erasurecode.rawcoder.util.RSUtil2;
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import java.nio.ByteBuffer;
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import java.util.Arrays;
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@ -35,7 +34,7 @@ import java.util.Arrays;
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* from HDFS-RAID, and also compatible with the native/ISA-L coder.
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*/
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@InterfaceAudience.Private
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public class RSRawDecoder2 extends AbstractRawErasureDecoder {
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public class RSRawDecoder extends AbstractRawErasureDecoder {
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//relevant to schema and won't change during decode calls
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private byte[] encodeMatrix;
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@ -55,7 +54,7 @@ public class RSRawDecoder2 extends AbstractRawErasureDecoder {
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private int numErasedDataUnits;
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private boolean[] erasureFlags;
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public RSRawDecoder2(int numDataUnits, int numParityUnits) {
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public RSRawDecoder(int numDataUnits, int numParityUnits) {
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super(numDataUnits, numParityUnits);
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if (numDataUnits + numParityUnits >= RSUtil.GF.getFieldSize()) {
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throw new HadoopIllegalArgumentException(
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@ -64,7 +63,7 @@ public class RSRawDecoder2 extends AbstractRawErasureDecoder {
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int numAllUnits = getNumDataUnits() + numParityUnits;
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encodeMatrix = new byte[numAllUnits * getNumDataUnits()];
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RSUtil2.genCauchyMatrix(encodeMatrix, numAllUnits, getNumDataUnits());
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RSUtil.genCauchyMatrix(encodeMatrix, numAllUnits, getNumDataUnits());
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if (isAllowingVerboseDump()) {
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DumpUtil.dumpMatrix(encodeMatrix, numDataUnits, numAllUnits);
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}
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@ -79,7 +78,7 @@ public class RSRawDecoder2 extends AbstractRawErasureDecoder {
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for (int i = 0; i < getNumDataUnits(); i++) {
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realInputs[i] = inputs[validIndexes[i]];
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}
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RSUtil2.encodeData(gfTables, realInputs, outputs);
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RSUtil.encodeData(gfTables, realInputs, outputs);
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}
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@Override
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@ -94,7 +93,7 @@ public class RSRawDecoder2 extends AbstractRawErasureDecoder {
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realInputs[i] = inputs[validIndexes[i]];
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realInputOffsets[i] = inputOffsets[validIndexes[i]];
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}
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RSUtil2.encodeData(gfTables, dataLen, realInputs, realInputOffsets,
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RSUtil.encodeData(gfTables, dataLen, realInputs, realInputOffsets,
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outputs, outputOffsets);
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}
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@ -131,7 +130,7 @@ public class RSRawDecoder2 extends AbstractRawErasureDecoder {
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generateDecodeMatrix(erasedIndexes);
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RSUtil2.initTables(getNumDataUnits(), erasedIndexes.length,
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RSUtil.initTables(getNumDataUnits(), erasedIndexes.length,
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decodeMatrix, 0, gfTables);
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if (isAllowingVerboseDump()) {
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System.out.println(DumpUtil.bytesToHex(gfTables, -1));
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@ -21,7 +21,6 @@ import org.apache.hadoop.HadoopIllegalArgumentException;
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import org.apache.hadoop.classification.InterfaceAudience;
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import org.apache.hadoop.io.erasurecode.rawcoder.util.DumpUtil;
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import org.apache.hadoop.io.erasurecode.rawcoder.util.RSUtil;
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import org.apache.hadoop.io.erasurecode.rawcoder.util.RSUtil2;
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import java.nio.ByteBuffer;
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@ -32,7 +31,7 @@ import java.nio.ByteBuffer;
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* from HDFS-RAID, and also compatible with the native/ISA-L coder.
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*/
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@InterfaceAudience.Private
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public class RSRawEncoder2 extends AbstractRawErasureEncoder {
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public class RSRawEncoder extends AbstractRawErasureEncoder {
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// relevant to schema and won't change during encode calls.
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private byte[] encodeMatrix;
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/**
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@ -41,7 +40,7 @@ public class RSRawEncoder2 extends AbstractRawErasureEncoder {
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*/
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private byte[] gfTables;
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public RSRawEncoder2(int numDataUnits, int numParityUnits) {
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public RSRawEncoder(int numDataUnits, int numParityUnits) {
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super(numDataUnits, numParityUnits);
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if (numDataUnits + numParityUnits >= RSUtil.GF.getFieldSize()) {
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@ -50,12 +49,12 @@ public class RSRawEncoder2 extends AbstractRawErasureEncoder {
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}
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encodeMatrix = new byte[getNumAllUnits() * numDataUnits];
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RSUtil2.genCauchyMatrix(encodeMatrix, getNumAllUnits(), numDataUnits);
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RSUtil.genCauchyMatrix(encodeMatrix, getNumAllUnits(), numDataUnits);
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if (isAllowingVerboseDump()) {
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DumpUtil.dumpMatrix(encodeMatrix, numDataUnits, getNumAllUnits());
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}
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gfTables = new byte[getNumAllUnits() * numDataUnits * 32];
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RSUtil2.initTables(numDataUnits, numParityUnits, encodeMatrix,
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RSUtil.initTables(numDataUnits, numParityUnits, encodeMatrix,
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numDataUnits * numDataUnits, gfTables);
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if (isAllowingVerboseDump()) {
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System.out.println(DumpUtil.bytesToHex(gfTables, -1));
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@ -64,13 +63,13 @@ public class RSRawEncoder2 extends AbstractRawErasureEncoder {
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@Override
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protected void doEncode(ByteBuffer[] inputs, ByteBuffer[] outputs) {
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RSUtil2.encodeData(gfTables, inputs, outputs);
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RSUtil.encodeData(gfTables, inputs, outputs);
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}
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@Override
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protected void doEncode(byte[][] inputs, int[] inputOffsets,
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int dataLen, byte[][] outputs, int[] outputOffsets) {
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RSUtil2.encodeData(gfTables, dataLen, inputs, inputOffsets, outputs,
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RSUtil.encodeData(gfTables, dataLen, inputs, inputOffsets, outputs,
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outputOffsets);
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}
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}
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@ -20,18 +20,18 @@ package org.apache.hadoop.io.erasurecode.rawcoder;
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import org.apache.hadoop.classification.InterfaceAudience;
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/**
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* A raw coder factory for raw Reed-Solomon coder in Java.
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* A raw coder factory for the new raw Reed-Solomon coder in Java.
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*/
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@InterfaceAudience.Private
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public class RSRawErasureCoderFactory2 implements RawErasureCoderFactory {
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public class RSRawErasureCoderFactory implements RawErasureCoderFactory {
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@Override
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public RawErasureEncoder createEncoder(int numDataUnits, int numParityUnits) {
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return new RSRawEncoder2(numDataUnits, numParityUnits);
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return new RSRawEncoder(numDataUnits, numParityUnits);
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}
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@Override
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public RawErasureDecoder createDecoder(int numDataUnits, int numParityUnits) {
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return new RSRawDecoder2(numDataUnits, numParityUnits);
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return new RSRawDecoder(numDataUnits, numParityUnits);
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}
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}
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@ -19,11 +19,16 @@ package org.apache.hadoop.io.erasurecode.rawcoder.util;
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import org.apache.hadoop.classification.InterfaceAudience;
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import java.nio.ByteBuffer;
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/**
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* Utilities for implementing Reed-Solomon code, used by RS coder.
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* Utilities for implementing Reed-Solomon code, used by RS coder. Some of the
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* codes are borrowed from ISA-L implementation (C or ASM codes).
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*/
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@InterfaceAudience.Private
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public class RSUtil {
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public final class RSUtil {
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private RSUtil(){}
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// We always use the byte system (with symbol size 8, field size 256,
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// primitive polynomial 285, and primitive root 2).
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@ -39,4 +44,144 @@ public class RSUtil {
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return primitivePower;
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}
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public static void initTables(int k, int rows, byte[] codingMatrix,
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int matrixOffset, byte[] gfTables) {
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int i, j;
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int offset = 0, idx = matrixOffset;
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for (i = 0; i < rows; i++) {
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for (j = 0; j < k; j++) {
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GF256.gfVectMulInit(codingMatrix[idx++], gfTables, offset);
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offset += 32;
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}
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}
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}
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/**
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* Ported from Intel ISA-L library.
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*/
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public static void genCauchyMatrix(byte[] a, int m, int k) {
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// Identity matrix in high position
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for (int i = 0; i < k; i++) {
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a[k * i + i] = 1;
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}
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// For the rest choose 1/(i + j) | i != j
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int pos = k * k;
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for (int i = k; i < m; i++) {
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for (int j = 0; j < k; j++) {
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a[pos++] = GF256.gfInv((byte) (i ^ j));
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}
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}
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}
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/**
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* Encode a group of inputs data and generate the outputs. It's also used for
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* decoding because, in this implementation, encoding and decoding are
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* unified.
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*
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* The algorithm is ported from Intel ISA-L library for compatible. It
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* leverages Java auto-vectorization support for performance.
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*/
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public static void encodeData(byte[] gfTables, int dataLen, byte[][] inputs,
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int[] inputOffsets, byte[][] outputs,
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int[] outputOffsets) {
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int numInputs = inputs.length;
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int numOutputs = outputs.length;
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int l, i, j, iPos, oPos;
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byte[] input, output;
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byte s;
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final int times = dataLen / 8;
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final int extra = dataLen - dataLen % 8;
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byte[] tableLine;
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for (l = 0; l < numOutputs; l++) {
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output = outputs[l];
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for (j = 0; j < numInputs; j++) {
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input = inputs[j];
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iPos = inputOffsets[j];
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oPos = outputOffsets[l];
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s = gfTables[j * 32 + l * numInputs * 32 + 1];
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tableLine = GF256.gfMulTab()[s & 0xff];
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/**
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* Purely for performance, assuming we can use 8 bytes in the SIMD
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* instruction. Subject to be improved.
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*/
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for (i = 0; i < times; i++, iPos += 8, oPos += 8) {
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output[oPos + 0] ^= tableLine[0xff & input[iPos + 0]];
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output[oPos + 1] ^= tableLine[0xff & input[iPos + 1]];
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output[oPos + 2] ^= tableLine[0xff & input[iPos + 2]];
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output[oPos + 3] ^= tableLine[0xff & input[iPos + 3]];
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output[oPos + 4] ^= tableLine[0xff & input[iPos + 4]];
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output[oPos + 5] ^= tableLine[0xff & input[iPos + 5]];
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output[oPos + 6] ^= tableLine[0xff & input[iPos + 6]];
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output[oPos + 7] ^= tableLine[0xff & input[iPos + 7]];
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}
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/**
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* For the left bytes, do it one by one.
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*/
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for (i = extra; i < dataLen; i++, iPos++, oPos++) {
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output[oPos] ^= tableLine[0xff & input[iPos]];
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}
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}
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}
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}
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/**
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* See above. Try to use the byte[] version when possible.
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*/
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public static void encodeData(byte[] gfTables, ByteBuffer[] inputs,
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ByteBuffer[] outputs) {
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int numInputs = inputs.length;
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int numOutputs = outputs.length;
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int dataLen = inputs[0].remaining();
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int l, i, j, iPos, oPos;
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ByteBuffer input, output;
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byte s;
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final int times = dataLen / 8;
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final int extra = dataLen - dataLen % 8;
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byte[] tableLine;
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for (l = 0; l < numOutputs; l++) {
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output = outputs[l];
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for (j = 0; j < numInputs; j++) {
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input = inputs[j];
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iPos = input.position();
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oPos = output.position();
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s = gfTables[j * 32 + l * numInputs * 32 + 1];
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tableLine = GF256.gfMulTab()[s & 0xff];
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for (i = 0; i < times; i++, iPos += 8, oPos += 8) {
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output.put(oPos + 0, (byte) (output.get(oPos + 0) ^
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tableLine[0xff & input.get(iPos + 0)]));
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output.put(oPos + 1, (byte) (output.get(oPos + 1) ^
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tableLine[0xff & input.get(iPos + 1)]));
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output.put(oPos + 2, (byte) (output.get(oPos + 2) ^
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tableLine[0xff & input.get(iPos + 2)]));
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output.put(oPos + 3, (byte) (output.get(oPos + 3) ^
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tableLine[0xff & input.get(iPos + 3)]));
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output.put(oPos + 4, (byte) (output.get(oPos + 4) ^
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tableLine[0xff & input.get(iPos + 4)]));
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output.put(oPos + 5, (byte) (output.get(oPos + 5) ^
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tableLine[0xff & input.get(iPos + 5)]));
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output.put(oPos + 6, (byte) (output.get(oPos + 6) ^
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tableLine[0xff & input.get(iPos + 6)]));
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output.put(oPos + 7, (byte) (output.get(oPos + 7) ^
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tableLine[0xff & input.get(iPos + 7)]));
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}
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for (i = extra; i < dataLen; i++, iPos++, oPos++) {
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output.put(oPos, (byte) (output.get(oPos) ^
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tableLine[0xff & input.get(iPos)]));
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}
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}
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}
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}
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}
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@ -1,172 +0,0 @@
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/**
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* Licensed to the Apache Software Foundation (ASF) under one
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* or more contributor license agreements. See the NOTICE file
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* distributed with this work for additional information
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* regarding copyright ownership. The ASF licenses this file
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* to you under the Apache License, Version 2.0 (the
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* "License"); you may not use this file except in compliance
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* with the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package org.apache.hadoop.io.erasurecode.rawcoder.util;
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import org.apache.hadoop.classification.InterfaceAudience;
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import java.nio.ByteBuffer;
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/**
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* Utilities for implementing Reed-Solomon code, used by RS2 coder. Some of the
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* codes are borrowed from ISA-L implementation (C or ASM codes).
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*/
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@InterfaceAudience.Private
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public final class RSUtil2 {
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private RSUtil2() { }
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public static void initTables(int k, int rows, byte[] codingMatrix,
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int matrixOffset, byte[] gfTables) {
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int i, j;
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int offset = 0, idx = matrixOffset;
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for (i = 0; i < rows; i++) {
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for (j = 0; j < k; j++) {
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GF256.gfVectMulInit(codingMatrix[idx++], gfTables, offset);
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offset += 32;
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}
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}
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}
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/**
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* Ported from Intel ISA-L library.
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*/
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public static void genCauchyMatrix(byte[] a, int m, int k) {
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// Identity matrix in high position
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for (int i = 0; i < k; i++) {
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a[k * i + i] = 1;
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}
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// For the rest choose 1/(i + j) | i != j
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int pos = k * k;
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for (int i = k; i < m; i++) {
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for (int j = 0; j < k; j++) {
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a[pos++] = GF256.gfInv((byte) (i ^ j));
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}
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}
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}
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/**
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* Encode a group of inputs data and generate the outputs. It's also used for
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* decoding because, in this implementation, encoding and decoding are
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* unified.
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*
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* The algorithm is ported from Intel ISA-L library for compatible. It
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* leverages Java auto-vectorization support for performance.
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*/
|
||||
public static void encodeData(byte[] gfTables, int dataLen, byte[][] inputs,
|
||||
int[] inputOffsets, byte[][] outputs,
|
||||
int[] outputOffsets) {
|
||||
int numInputs = inputs.length;
|
||||
int numOutputs = outputs.length;
|
||||
int l, i, j, iPos, oPos;
|
||||
byte[] input, output;
|
||||
byte s;
|
||||
final int times = dataLen / 8;
|
||||
final int extra = dataLen - dataLen % 8;
|
||||
byte[] tableLine;
|
||||
|
||||
for (l = 0; l < numOutputs; l++) {
|
||||
output = outputs[l];
|
||||
|
||||
for (j = 0; j < numInputs; j++) {
|
||||
input = inputs[j];
|
||||
iPos = inputOffsets[j];
|
||||
oPos = outputOffsets[l];
|
||||
|
||||
s = gfTables[j * 32 + l * numInputs * 32 + 1];
|
||||
tableLine = GF256.gfMulTab()[s & 0xff];
|
||||
|
||||
/**
|
||||
* Purely for performance, assuming we can use 8 bytes in the SIMD
|
||||
* instruction. Subject to be improved.
|
||||
*/
|
||||
for (i = 0; i < times; i++, iPos += 8, oPos += 8) {
|
||||
output[oPos + 0] ^= tableLine[0xff & input[iPos + 0]];
|
||||
output[oPos + 1] ^= tableLine[0xff & input[iPos + 1]];
|
||||
output[oPos + 2] ^= tableLine[0xff & input[iPos + 2]];
|
||||
output[oPos + 3] ^= tableLine[0xff & input[iPos + 3]];
|
||||
output[oPos + 4] ^= tableLine[0xff & input[iPos + 4]];
|
||||
output[oPos + 5] ^= tableLine[0xff & input[iPos + 5]];
|
||||
output[oPos + 6] ^= tableLine[0xff & input[iPos + 6]];
|
||||
output[oPos + 7] ^= tableLine[0xff & input[iPos + 7]];
|
||||
}
|
||||
|
||||
/**
|
||||
* For the left bytes, do it one by one.
|
||||
*/
|
||||
for (i = extra; i < dataLen; i++, iPos++, oPos++) {
|
||||
output[oPos] ^= tableLine[0xff & input[iPos]];
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* See above. Try to use the byte[] version when possible.
|
||||
*/
|
||||
public static void encodeData(byte[] gfTables, ByteBuffer[] inputs,
|
||||
ByteBuffer[] outputs) {
|
||||
int numInputs = inputs.length;
|
||||
int numOutputs = outputs.length;
|
||||
int dataLen = inputs[0].remaining();
|
||||
int l, i, j, iPos, oPos;
|
||||
ByteBuffer input, output;
|
||||
byte s;
|
||||
final int times = dataLen / 8;
|
||||
final int extra = dataLen - dataLen % 8;
|
||||
byte[] tableLine;
|
||||
|
||||
for (l = 0; l < numOutputs; l++) {
|
||||
output = outputs[l];
|
||||
|
||||
for (j = 0; j < numInputs; j++) {
|
||||
input = inputs[j];
|
||||
iPos = input.position();
|
||||
oPos = output.position();
|
||||
|
||||
s = gfTables[j * 32 + l * numInputs * 32 + 1];
|
||||
tableLine = GF256.gfMulTab()[s & 0xff];
|
||||
|
||||
for (i = 0; i < times; i++, iPos += 8, oPos += 8) {
|
||||
output.put(oPos + 0, (byte) (output.get(oPos + 0) ^
|
||||
tableLine[0xff & input.get(iPos + 0)]));
|
||||
output.put(oPos + 1, (byte) (output.get(oPos + 1) ^
|
||||
tableLine[0xff & input.get(iPos + 1)]));
|
||||
output.put(oPos + 2, (byte) (output.get(oPos + 2) ^
|
||||
tableLine[0xff & input.get(iPos + 2)]));
|
||||
output.put(oPos + 3, (byte) (output.get(oPos + 3) ^
|
||||
tableLine[0xff & input.get(iPos + 3)]));
|
||||
output.put(oPos + 4, (byte) (output.get(oPos + 4) ^
|
||||
tableLine[0xff & input.get(iPos + 4)]));
|
||||
output.put(oPos + 5, (byte) (output.get(oPos + 5) ^
|
||||
tableLine[0xff & input.get(iPos + 5)]));
|
||||
output.put(oPos + 6, (byte) (output.get(oPos + 6) ^
|
||||
tableLine[0xff & input.get(iPos + 6)]));
|
||||
output.put(oPos + 7, (byte) (output.get(oPos + 7) ^
|
||||
tableLine[0xff & input.get(iPos + 7)]));
|
||||
}
|
||||
|
||||
for (i = extra; i < dataLen; i++, iPos++, oPos++) {
|
||||
output.put(oPos, (byte) (output.get(oPos) ^
|
||||
tableLine[0xff & input.get(iPos)]));
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
@ -19,7 +19,7 @@ package org.apache.hadoop.io.erasurecode.coder;
|
|||
|
||||
import org.apache.hadoop.conf.Configuration;
|
||||
import org.apache.hadoop.fs.CommonConfigurationKeys;
|
||||
import org.apache.hadoop.io.erasurecode.rawcoder.RSRawErasureCoderFactoryLegacy;
|
||||
import org.apache.hadoop.io.erasurecode.rawcoder.RSRawErasureCoderFactory;
|
||||
import org.junit.Before;
|
||||
import org.junit.Test;
|
||||
|
||||
|
|
@ -51,7 +51,7 @@ public class TestHHXORErasureCoder extends TestHHErasureCoderBase {
|
|||
*/
|
||||
Configuration conf = new Configuration();
|
||||
conf.set(CommonConfigurationKeys.IO_ERASURECODE_CODEC_RS_RAWCODER_KEY,
|
||||
RSRawErasureCoderFactoryLegacy.class.getCanonicalName());
|
||||
RSRawErasureCoderFactory.class.getCanonicalName());
|
||||
prepare(conf, 10, 4, new int[]{0}, new int[0]);
|
||||
|
||||
testCoding(true);
|
||||
|
|
|
|||
|
|
@ -19,7 +19,7 @@ package org.apache.hadoop.io.erasurecode.coder;
|
|||
|
||||
import org.apache.hadoop.conf.Configuration;
|
||||
import org.apache.hadoop.fs.CommonConfigurationKeys;
|
||||
import org.apache.hadoop.io.erasurecode.rawcoder.RSRawErasureCoderFactoryLegacy;
|
||||
import org.apache.hadoop.io.erasurecode.rawcoder.RSRawErasureCoderFactory;
|
||||
import org.junit.Before;
|
||||
import org.junit.Rule;
|
||||
import org.junit.Test;
|
||||
|
|
@ -58,7 +58,7 @@ public class TestRSErasureCoder extends TestErasureCoderBase {
|
|||
*/
|
||||
Configuration conf = new Configuration();
|
||||
conf.set(CommonConfigurationKeys.IO_ERASURECODE_CODEC_RS_RAWCODER_KEY,
|
||||
RSRawErasureCoderFactoryLegacy.class.getCanonicalName());
|
||||
RSRawErasureCoderFactory.class.getCanonicalName());
|
||||
prepare(conf, 10, 4, new int[]{0}, new int[0]);
|
||||
|
||||
testCoding(true);
|
||||
|
|
|
|||
|
|
@ -22,12 +22,12 @@ import org.junit.Before;
|
|||
/**
|
||||
* Test the new raw Reed-solomon coder implemented in Java.
|
||||
*/
|
||||
public class TestRSRawCoder2 extends TestRSRawCoderBase {
|
||||
public class TestRSRawCoder extends TestRSRawCoderBase {
|
||||
|
||||
@Before
|
||||
public void setup() {
|
||||
this.encoderClass = RSRawEncoder2.class;
|
||||
this.decoderClass = RSRawDecoder2.class;
|
||||
this.encoderClass = RSRawEncoder.class;
|
||||
this.decoderClass = RSRawDecoder.class;
|
||||
setAllowDump(false);
|
||||
}
|
||||
}
|
||||
Loading…
Reference in New Issue