Good to know. Will look into the Raspberry Pi 4 (w/4GB RAM).
In general, are there any tuning or configuration tips/tricks for very
memory-constrained deployments (e.g., 1-4GB RAM)?
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I don't think Spark is meant to run with 1GB of memory on the entire system.
The JVM loads almost 200MB of bytecode, and each page during query processing
takes a min of 64MB.
Maybe on the 4GB model of raspberry pi 4.
On Wed, Jul 10, 2019 at 7:57 AM, agg212 < alexander_galaka...@brown.edu >
We are trying to benchmark TPC-H (scale factor 1) on a 13-node Raspberry Pi
3B+ cluster (1 master, 12 workers). Each node has 1GB of RAM and a quad-core
processor, running Ubuntu Server 18.04. The cluster is using the Spark
standalone scheduler with the *.tbl files from TPCH’s dbgen tool stored in
