In Hbase, I have configured hbase.hregion.max.filesize as 10GB. If the Single row exceeds the 10GB size, then the row will not into 2 regions as Hbase splits are done based on row key
For example, if I have a row which has 1000 columns, and each column varies between 25MB to 40 MB. So there is chance to exceed the defined region size. If this is the case, how will it affect the performance while reading data using rowkey alone or row-key with column qualifier?
First thing is Hbase is NOT for storing that much big data 10GB in a single row(its quite hypothetical).
I hope your have not saved 10GB in a single row (just thinking of saving that)
It will adversely affect the performance. You consider other ways like storing this much data in hdfs in a partitioned structure.
In general, these are the tips for generally applicable batch clients like Mapreduce Hbase jobs
Scan scan = new Scan();
scan.setCaching(500); //1 is the default in Scan, which will be bad for MapReduce jobs
scan.setCacheBlocks(false); // don't set to true for MR jobs
Can have look at Performance