【发布时间】:2014-02-12 02:51:12
【问题描述】:
我将少量数据(几 MB)存储在分布式缓存中,并使用它对两个大文件执行反连接。对于缓存中的几行数据,该功能运行良好,但是当缓存在生产中有更多数据时,它无法完成这项工作,但也不会引发任何错误。只是只有少数记录(约 20%)被加入,而其他记录则被忽略。那么分布式缓存中可以存储的记录数有上限吗?为什么它为某些记录工作而忽略其余记录?任何建议都会非常有帮助。 下面是我的代码
public class MyMapper extends Mapper<LongWritable, Text, Text, TextPair> {
Text albumKey = new Text();
Text photoKey = new Text();
private HashSet<String> photoDeleted = new HashSet<String>();
private HashSet<String> albDeleted = new HashSet<String>();
Text interKey = new Text();
private TextPair interValue = new TextPair();
private static final Logger LOGGER = Logger.getLogger(SharedStreamsSlMapper.class);
protected void setup(Context context) throws IOException, InterruptedException {
int count=0;
Path[] cacheFiles = DistributedCache.getLocalCacheFiles(context.getConfiguration());
System.out.println(cacheFiles.length);
LOGGER.info(cacheFiles+"****");
try {
if (cacheFiles != null && cacheFiles.length > 0) {
for (Path path : cacheFiles) {
String line;
String[] tokens;
BufferedReader joinReader = new BufferedReader(new FileReader(path.toString()));
System.out.println(path.toString());
// BufferedReader joinReader = new BufferedReader(new FileReader("/Users/Kunal_Basak/Desktop/ss_test/dsitCache/part-m-00000"));
try {
while ((line = joinReader.readLine()) != null) {
count++;
tokens = line.split(SSConstants.TAB, 2);
if(tokens.length<2){
System.out.println("WL");
continue;
}
if (tokens[0].equals("P")) {
photoDeleted.add(tokens[1]);
}
else if (tokens[0].equals("A")) {
albDeleted.add(tokens[1]);
}
}
}
finally {
joinReader.close();
}
}
}
}
catch (IOException e) {
System.out.println("Exception reading DistributedCache: " + e);
}
System.out.println(count);
System.out.println("albdeleted *****"+albDeleted.size());
System.out.println("photo deleted *****"+photoDeleted.size());
LOGGER.info("albdeleted *****"+albDeleted.size());
LOGGER.info("albdeleted *****"+albDeleted.size());
}
public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
try{
//my mapper code
}
}
}
【问题讨论】:
-
当你打印出缓存文件的数量时,是和你预期的一样,还是有些文件丢失了?
标签: hadoop mapreduce distributed-caching