apache spark - Why is my executor memory usage stuck at 0? -


i have pretty simple spark job looks this:

javapairrdd<key,value> rawdata = newaccumulordd(...); javapairrdd<key,value> indexsrc =     rawdata.filter(new indexfilter()).cache(); javapairrdd<key,value> indexentries =     indexsrc.mappartitionstopair(new indexbuilder(numpartitions)); javapairrdd<key,value> reverseindexentries =     indexsrc.mappartitionstopair(new reverseindexbuilder(numpartitions)); javapairrdd<key,value> dataentries =     rawdata.mappartitionstopair(new databuilder(numpartitions)).cache();  dataentries.union(indexentries)   .union(reverseindexentries)   .repartitionandsortwithinpartitions(new partitionedindexrddpartitioner(num_bins))   .saveasnewapihadoopfile(pidxbulk.tostring(), key.class, value.class,       accumulofileoutputformat.class, conf);

where key , value apache accumulo's key , value classes (using kryoserializer).

i'm not sure put calls cache(), or if they're needed @ all. i'm concerned executors don't seem using of memory i've allocated them:

screenshot showing 0 memory used

and "storage" page in application ui empty.

am doing wrong, or has spark decided can't make job go faster storing rdds?

memory used means memory used caching.

in code performing 1 action , indexsrc or dataentries not used again, there not point of caching it.

to prove it, can add

indexsrc.count(); , dataentries.count(); after declaring them , check executor/storage page.

javapairrdd<key,value> rawdata = newaccumulordd(...); javapairrdd<key,value> indexsrc = rawdata.filter(new indexfilter()).cache(); indexsrc.count(); javapairrdd<key,value> indexentries = indexsrc.mappartitionstopair(new indexbuilder(numpartitions)); javapairrdd<key,value> reverseindexentries = indexsrc.mappartitionstopair(new reverseindexbuilder(numpartitions)); javapairrdd<key,value> dataentries = rawdata.mappartitionstopair(new databuilder(numpartitions)).cache(); dataentries.count();  dataentries.union(indexentries)   .union(reverseindexentries)   .repartitionandsortwithinpartitions(new partitionedindexrddpartitioner(num_bins))   .saveasnewapihadoopfile(pidxbulk.tostring(), key.class, value.class,       accumulofileoutputformat.class, conf);

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