[GitHub] [arrow-datafusion] alamb commented on a diff in pull request #6172: Add parquet filter and sort to bench.sh

["alamb (via GitHub)" <gi...@apache.org>]

alamb commented on code in PR #6172:
URL: https://github.com/apache/arrow-datafusion/pull/6172#discussion_r1184002980


##########
benchmarks/bench.sh:
##########
@@ -247,6 +257,22 @@ run_tpch_mem() {
     $CARGO_COMMAND --bin tpch -- benchmark datafusion --iterations 5 --path "${DATA_DIR}" -m --format parquet -o ${RESULTS_FILE}
 }
 
+# Runs the parquet filter benchmark
+run_parquet() {
+    RESULTS_FILE="${RESULTS_DIR}/parquet.json"
+    echo "RESULTS_FILE: ${RESULTS_FILE}"
+    echo "Running parquet filter benchmark..."
+    $CARGO_COMMAND --bin parquet -- filter --path "${DATA_DIR}" --scale-factor 1.0 --iterations 5 -o ${RESULTS_FILE}

Review Comment:
   This is even more confusing -- the scale factor for tpch is actually a applied, but it is applied when we create the data. Specifically
   
   https://github.com/apache/arrow-datafusion/blob/2787e7a36a6be83d91201df20827d3695f933300/benchmarks/bench.sh#L202
   
   The "parquet" benchmark actually doesn't use the tpch dataset at all, and instead generates its own data. Hwever, it overloads the "scale factor" terminology to describe the relative sizes



##########
benchmarks/bench.sh:
##########
@@ -247,6 +257,22 @@ run_tpch_mem() {
     $CARGO_COMMAND --bin tpch -- benchmark datafusion --iterations 5 --path "${DATA_DIR}" -m --format parquet -o ${RESULTS_FILE}
 }
 
+# Runs the parquet filter benchmark
+run_parquet() {
+    RESULTS_FILE="${RESULTS_DIR}/parquet.json"
+    echo "RESULTS_FILE: ${RESULTS_FILE}"
+    echo "Running parquet filter benchmark..."
+    $CARGO_COMMAND --bin parquet -- filter --path "${DATA_DIR}" --scale-factor 1.0 --iterations 5 -o ${RESULTS_FILE}

Review Comment:
   It is somewhat ugly to have to run a second command(`parquet`)  for different benchmarks -- I plan to combine them into a single benchmark runner over time



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