Pavan, How large are the rows in HBase? 22 million rows is not very much but you mentioned "huge strings". Can you tell which part of the processing is the limiting factor (read from HBase, mapper output, reducers)? John
From: Pavan Sudheendra [mailto:pavan0...@gmail.com] Sent: Saturday, September 21, 2013 2:17 AM To: user@hadoop.apache.org Subject: Re: How to best decide mapper output/reducer input for a huge string? No, I don't have a combiner in place. Is it necessary? How do I make my map output compressed? Yes, the Tables in HBase are compressed. Although, there's no real bottleneck, the time it takes to process the entire table is huge. I have to constantly check if i can optimize it somehow.. Oh okay.. I'll implement a Custom Writable.. Apart from that, do you see any thing wrong with my design? Does it require any kind of re-work? Thank you so much for helping.. On Sat, Sep 21, 2013 at 1:06 PM, Pradeep Gollakota <pradeep...@gmail.com<mailto:pradeep...@gmail.com>> wrote: One thing that comes to mind is that your keys are Strings which are highly inefficient. You might get a lot better performance if you write a custom writable for your Key object using the appropriate data types. For example, use a long (LongWritable) for timestamps. This should make (de)serialization a lot faster. If HouseHoldId is an integer, your speed of comparisons for sorting will also go up. Ensure that your map output's are being compressed. Are your tables in HBase compressed? Do you have a combiner? Have you been able to profile your code to see where the bottlenecks are? On Sat, Sep 21, 2013 at 12:04 AM, Pavan Sudheendra <pavan0...@gmail.com<mailto:pavan0...@gmail.com>> wrote: Hi Pradeep, Yes.. Basically i'm only writing the key part as the map output.. The V of <K,V> is not of much use to me.. But i'm hoping to change that if it leads to faster execution.. I'm kind of a newbie so looking to make the map/reduce job run a lot faster.. Also, yes. It gets sorted by the HouseHoldID which is what i needed.. But seems if i write a map output for each and every row of a 19 m row HBase table, its taking nearly a day to complete.. (21 mappers and 21 reducers) I have looked at both Pig/Hive to do the job but i'm supposed to do this via a MR job.. So, cannot use either of that.. Do you recommend me to try something if i have the data in that format? On Sat, Sep 21, 2013 at 12:26 PM, Pradeep Gollakota <pradeep...@gmail.com<mailto:pradeep...@gmail.com>> wrote: I'm sorry but I don't understand your question. Is the output of the mapper you're describing the key portion? If it is the key, then your data should already be sorted by HouseHoldId since it occurs first in your key. The SortComparator will tell Hadoop how to sort your data. So you use this if you have a need for a non lexical sort order. The GroupingComparator will tell Hadoop how to group your data for the reducer. All KV-pairs from the same group will be given to the same Reducer. If your reduce computation needs all the KV-pairs for the same HouseHoldId, then you will need to write a GroupingComparator. Also, have you considered using a higher level abstraction on Hadoop such as Pig, Hive, Cascading, etc.? The sorting/grouping type of tasks are a LOT easier to write in these languages. Hope this helps! - Pradeep On Fri, Sep 20, 2013 at 11:32 PM, Pavan Sudheendra <pavan0...@gmail.com<mailto:pavan0...@gmail.com>> wrote: I need to improve my MR jobs which uses HBase as source as well as sink.. Basically, i'm reading data from 3 HBase Tables in the mapper, writing them out as one huge string for the reducer to do some computation and dump into a HBase Table.. Table1 ~ 19 million rows. Table2 ~ 2 million rows. Table3 ~ 900,000 rows. The output of the mapper is something like this : HouseHoldId contentID name duration genre type channelId personId televisionID timestamp I'm interested in sorting it on the basis of the HouseHoldID value so i'm using this technique. I'm not interested in the V part of pair so i'm kind of ignoring it. My mapper class is defined as follows: public static class AnalyzeMapper extends TableMapper<Text, IntWritable> { } For my MR job to be completed, it takes 22 hours to complete which is not desirable at all. I'm supposed to optimize this somehow to run a lot faster somehow.. scan.setCaching(750); scan.setCacheBlocks(false); TableMapReduceUtil.initTableMapperJob ( Table1, // input HBase table name scan, AnalyzeMapper.class, // mapper Text.class, // mapper output key IntWritable.class, // mapper output value job); TableMapReduceUtil.initTableReducerJob( OutputTable, // output table AnalyzeReducerTable.class, // reducer class job); job.setNumReduceTasks(RegionCount); My HBase Table1 has 21 regions so 21 mappers are spawned. We are running a 8 node cloudera cluster. Should i use a custom SortComparator or a Group Comparator? -- Regards- Pavan -- Regards- Pavan -- Regards- Pavan
