[ http://issues.apache.org/jira/browse/HADOOP-234?page=comments#action_12412962 ]
Milind Bhandarkar commented on HADOOP-234: ------------------------------------------ This can be done by providing just one C++ class in record IO. Currently, C++ version for record IO generates methods for each class that read from and write to InStream and OutStream interfaces, that contain only read and write methods. Creation of concrete classes that implement these interfaces is outside of the code generation. One could proovide a byteStream class in C++ that provides these interfaces. The construction of BytesOutStream happens in C++ and after serializing C++ record, this stream goes to Java via JNI, which is then converted to BytesWritable and written to the sequencefile. BytesInStream is created in Java tied with the sequencefile, and supplies bytes to the C++ record. > Support for writing Map/Reduce functions in C++ > ----------------------------------------------- > > Key: HADOOP-234 > URL: http://issues.apache.org/jira/browse/HADOOP-234 > Project: Hadoop > Type: New Feature > Components: mapred > Reporter: Sanjay Dahiya > > MapReduce C++ support > Requirements > 1. Allow users to write Map and Reduce functions in C++, rest of the > infrastructure already present in Java should be reused. > 2. Avoid users having to write both Java and C++ for this to work. > 3. Avoid users having to work with JNI methods directly by wrapping them in > helper functions. > 4. Use Record IO for describing record format, both MR java framework and C++ > should > use the same format to work seemlessly. > 5. Allow users to write simple map reduce tasks without learning record IO if > keys and values are > simple strings. > Implementation notes > - If keys and values are simple strings then user passes SimpleNativeMapper > in JobConf and implements > mapper and reducer methods in C++. > - For composite Record IO types user starts with defining a record format > using Record IO DDL. > - User generates Java and C++ classes from the DDL using record IO. > - Users configures JobConf to use the generated Java classes as the MR > input/output, key/value classes. > - User writes Map and Reduce functions in C++ using a standard interface ( > given below ) , this interface > makes a serialized record IO format available to the C++ function which > should be deserialized in corrosponding > generated C++ record IO classes. > - User uses the helper functions to pass the serialized format of generated > output key/value pairs to output collector. > Following is a pseudocode for the Mapper ( Reducer can be implemented > similarly ) - > Native(JNI) Java proxy for the Mapper : > --------------------------------------- > Without Record IO :- > -------------------- > public class SimpleNativeMapper extends MapReduceBase implements Mapper { > /** > * Works on simple strings. > **/ > public void map(WritableComparable key, Writable value, > OutputCollector output, Reporter reporter) throws > IOException { > mapNative(key.toString().getBytes() > , value.toString().getBytes(), output, > reporter); > } > > /** > * Native implementation. > **/ > private native void mapNative(byte[] key, byte[] value, > OutputCollector output, Reporter reporter) throws > IOException; > } > With Record IO :- > ------------------ > public class RecordIONativeMapper extends MapReduceBase implements Mapper { > /** > * Implementation of map method, this acts as a JNI proxy for actual > map > * method implemented in C++. Works for Record IO based records. > * @see map(byte[] , byte[], OutputCollector, Reporter) > */ > public void map(WritableComparable key, Writable value, > OutputCollector output, Reporter reporter) throws > IOException { > > byte[] keyBytes = null ; > byte[] valueBytes = null ; > > try{ > // we need to serialize the key and record and pass the > serialized > // format to C++ / JNI methods so they can interpret it > using appropriate > // record IO classes. > { > ByteArrayOutputStream keyStream = new > ByteArrayOutputStream() ; > BinaryOutputArchive boa = new > BinaryOutputArchive(new DataOutputStream(keyStream)) ; > > ((Record)key).serialize(boa, "WhatIsTag"); > keyBytes = keyStream.toByteArray(); > } > { > ByteArrayOutputStream valueStream = new > ByteArrayOutputStream() ; > BinaryOutputArchive boa = new > BinaryOutputArchive(new DataOutputStream(valueStream)) ; > > ((Record)key).serialize(boa, "WhatIsTag"); > valueBytes = valueStream.toByteArray(); > } > }catch(ClassCastException e){ > // throw better exceptions > throw new IOException("Input record must be of Record > IO Type"); > } > // pass the serialized byte[] to C++ implementation. > mapNative(keyBytes, valueBytes, output, reporter); > } > /** > * Implementation in C++. > */ > private native void mapNative(byte[] key, byte[] value, > OutputCollector output, Reporter reporter) throws > IOException; > } > OutputCollector Proxy for C++ > ------------------------------ > public class NativeOutputCollector implements OutputCollector { > // standard method from interface > public void collect(WritableComparable key, Writable value) > throws IOException { > } > > // deserializes key and value and calls collect(WritableComparable, > Writable) > public void collectFromNative(byte[]key, byte[]value){ > // deserialize key and value to java types ( as configured in > JobConf ) > // call actual collect method > } > } > Core Native functions ( helper for user provided Mapper and Reducer ) > --------------------------------------------------------------------- > #include "org_apache_hadoop_mapred_NativeMapper.h" > #include "UserMapper.h" > /** > * A C++ proxy method, calls actual implementation of the Mapper. This > method > signature is generated by javah. > **/ > JNIEXPORT void JNICALL Java_org_apache_hadoop_mapred_NativeMapper_mapNative > (JNIEnv *env, jobject thisObj, jbyteArray key, jbyteArray value, > jobject output_collector, jobject reporter); > { > > // convert char* and pass on to user defined map method. > // user's map method should take care of converting it to correct > record IO > // type. > int keyLen = (*env)->GetArrayLength(env, key) ; > int valueLen = (*env)->GetArrayLength(env, valueLen) ; > const char *keyBuf = (*env)->GetByteArrayElements(env,key, keyLen, > JNI_FALSE) ; > const char *valueuf = (*env)->GetByteArrayElements(env,value, valueLen, > JNI_FALSE) ; > > // Call User defined method > user_map(keyBuf, valueBuf, output_collector, reporter) ; > > (*env)->ReleaseByteArrayElements(env, key, keyBuf, JNI_ABORT) ; > (*env)->ReleaseByteArrayElements(env, value, ValueBuf, JNI_ABORT) ; > } > /** > Helper method, acts as a proxy to OutputCollector in java. key and > value > must be serialized forms of records as specified in JobConf. > **/ > void output_collector(const char * key, const char *value, > jobject output_collector, jobject reporter){ > > // invoke java NativeOutputCollector.collect with key and value. > } > User defined Mapper ( and Reducer ) > ------------------------------------ > /** > implements user defined map operation. > **/ > void user_mapper(const char *key, const char *value, jobject collector, > jobject recorder) { > //1. deserialize key/value in the appropriate format using record IO. > > //2. process key/value and generate the intermediate key/values in > record IO format. > > //3. Deserialize intermediate key/values to intermed_key and > intermed_value > > //4. pass intermed_key/intermed_value using helper function - > // output_collector(intermed_key, intermed_value, > collector, recorder); > > > } -- This message is automatically generated by JIRA. - If you think it was sent incorrectly contact one of the administrators: http://issues.apache.org/jira/secure/Administrators.jspa - For more information on JIRA, see: http://www.atlassian.com/software/jira
