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I've seen redhat has come up one possible solution with GlusterFS working as the backend for hadoop. In this case, you can get ride of the namenode/datanode architecture and replace it with glusterfs, meanwhile you still have Hadoop Mapreduce api-compatibility.

Just wondering how does the performance compare against native-HDFS? Is it really production ready? Does it support all the hadoop ecosystem as well? e.g. Solr Cloud, Spark, Impala etc etc.

Shengjie
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disclaimer: I work for Storage vendor. Well. I don't know much about GlusterFS in particular but i can speak about Lustre as it's POSIX at the end of the day. It's parallel filesystem, but the benchmarks i looked into recently showed it does outperform HDFS. but it's definitely a production ready alternative that offers a single name space for your data (no more HDFS ingestion)

What does work from Hadoop ecosystem today? what I've seen in the production today is Spark,Hive,Hbase. Imapala looks to me it require certain parts of HDFS, this is why it doesn't work with POSIX FS and it's not HCFS. I did a quick test and i was able to create the database and everything, but i wasn't able to fetch any rows.

Let me if you need further help.

Abdulrahman Alkhamees
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  • Can you be a bit more specific on why it outperform HDFS? and what what parts of HDFS are required for some frameworks, e.g. Impala. – Shengjie Dec 10 '15 at 03:41
  • The benchmarks that I've seen shows that Lustre have less query execution time compared to HDFS. the whole idea of going with POSIX filesystem mainly focus on the following points 1- You skip the part of ingesting data into HDFS (this can take forever if you have a very large dataset). 2- you loose a lot of disk capacity with HDFS, POSIX FS implementation rely on enterprise RAID protection. For Impala, i am not sure what parts of the code need HDFS but i don't know as of today any Imapla runs on POSIX FS – Abdulrahman Alkhamees Dec 13 '15 at 18:10
  • Thanks very much for the explanation. – Shengjie Dec 14 '15 at 05:43