Hi guys,
I need help in implementing XG-Boost in PySpark.
As per the conversation in a popular thread regarding XGB goes, it is
available in Scala and Java versions but not Python. But, we've to
implement a pythonic distributed solution (on Spark) maybe using DMLC or
similar, to go ahead with
Nobody has any idea... ?
Is filtering after aggregation in structured streaming supported but maybe
buggy? See following line in the example from earlier mail...
...
.where(F.expr("distinct_username >= 2"))
...
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Hi,
w.r.t. ElementTrackingStore, since it is backed by KVStore, there should be
other classes which occupy significant memory.
Can you pastebin the top 10 entries among the heap dump ?
Thanks
I am trying to parallelize a simple Spark program processes HBASE data in
parallel.// Get Hbase RDD
JavaPairRDD hBaseRDD = jsc
.newAPIHadoopRDD(conf, TableInputFormat.class,
ImmutableBytesWritable.class, Result.class);
long