Sqljs upgrade and benchmark improvements (#103)

* Update to sql.js 1.7.0

* Update to emsdk 3.0.1, replace/remove deprecated/irrelevant settings

- Renamed .bc extension to .o
- Remove deprecated INLINING_LIMIT setting
- Remove SINGLE_FILE

* Update SQLite to 3.39.3

* Collect and plot CPU and RSS charts from the benchmark containers

* Move procpath commands to a playbook, plot only top 2 RSS & CPU usage

* Optimise for size, put -flto for both compile and link

lib/sql-js/benchmark/README.md

@@ -1,14 +1,25 @@
 # SQLite WebAssembly build micro-benchmark
 
-This directory contains a micro-benchmark for evaluating SQLite
-WebAssembly builds performance on typical SQL queries, run from
-`make.sh` script. It can also serve as a smoke test.
+This directory contains a micro-benchmark for evaluating SQLite WebAssembly
+builds performance on read and write SQL queries, run from `make.sh` script. If
+the script has permission to `nice` processes and [Procpath][1] is installed,
+e.g. it is run with `sudo -E env PATH=$PATH ./make.sh`, it'll `renice` all
+processes running inside the benchmark containers. It can also serve as a smoke
+test (e.g. for memory leaks).
 
-The benchmark operates on a set of SQLite WebAssembly builds expected
-in `lib/build-$NAME` directories each containing `sql-wasm.js` and
-`sql-wasm.wasm`. Then it creates a Docker image for each, and runs
-the benchmark in Firefox and Chromium using Karma in the container.
+The benchmark operates on a set of SQLite WebAssembly builds expected in
+`lib/build-$NAME` directories each containing `sql-wasm.js` and
+`sql-wasm.wasm`. Then it creates a Docker image for each, and runs the
+benchmark in Firefox and Chromium using Karma in the container.
 
-After successful run, the benchmark result of each build is contained
-in `build-$NAME-result.json`. The JSON result files can be analysed
-using `result-analysis.ipynb` Jupyter notebook.
+After successful run, the benchmark produces the following per each build:
+
+- `build-$NAME-result.json`
+- `build-$NAME.sqlite` (if Procpath is installed)
+- `build-$NAME.svg` (if Procpath is installed)
+
+These files can be analysed using `result-analysis.ipynb` Jupyter notebook.
+The SVG is a chart with CPU and RSS usage of each test container (i.e. Chromium
+run, then Firefox run per container).
+
+[1]: https://pypi.org/project/Procpath/

lib/sql-js/benchmark/make.sh

@@ -1,7 +1,8 @@
 #!/bin/bash -e
 
 cleanup () {
-  rm -rf lib/dist $flag_file
+  rm -rf lib/dist "$renice_flag_file"
+  docker rm -f sqljs-benchmark-run 2> /dev/null || true
 }
 trap cleanup EXIT
 
@@ -11,34 +12,36 @@ if [ ! -f sample.csv ]; then
     | gunzip -c > sample.csv
 fi
 
+PLAYBOOK=procpath/karma_docker.procpath
+
 # for renice to work run like "sudo -E env PATH=$PATH ./make.sh"
-test_ni=$(nice -n -1 nice)
-if [ $test_ni == -1 ]; then
-  flag_file=$(mktemp)
+test_ni=$(nice -n -5 nice)
+if [ $test_ni == -5 ]; then
+  renice_flag_file=$(mktemp)
 fi
-(
-  while [ -f $flag_file ]; do
-    root_pid=$(
-      docker ps -f status=running -f name='^sqljs-benchmark-' -q \
-        | xargs -r -I{} -- docker inspect -f '{{.State.Pid}}' {}
-    )
-    if [ ! -z $root_pid ]; then
-      procpath query -d $'\n' "$..children[?(@.stat.pid == $root_pid)]..pid" \
-        | xargs -I{} -- renice -n -1 -p {} > /dev/null
-    fi
-    sleep 1
-  done &
-)
+{
+  while [ -f $renice_flag_file ]; do
+    procpath --logging-level ERROR play -f $PLAYBOOK renice:watch
+  done
+} &
 
 shopt -s nullglob
 for d in lib/build-* ; do
   rm -rf lib/dist
   cp -r $d lib/dist
+  sample_name=$(basename $d)
 
-  name=$(basename $d)
-  docker build -t sqliteviz/sqljs-benchmark:$name .
-  docker rm sqljs-benchmark-$name 2> /dev/null || true
-  docker run -it --cpus 2 --name sqljs-benchmark-$name sqliteviz/sqljs-benchmark:$name
-  docker cp sqljs-benchmark-$name:/tmp/build/suite-result.json ${name}-result.json
-  docker rm sqljs-benchmark-$name
+  docker build -t sqliteviz/sqljs-benchmark .
+  docker rm sqljs-benchmark-run 2> /dev/null || true
+  docker run -d -it --cpus 2 --name sqljs-benchmark-run sqliteviz/sqljs-benchmark
+  {
+    rm -f ${sample_name}.sqlite
+    procpath play -f $PLAYBOOK -o database_file=${sample_name}.sqlite track:record
+    procpath play -f $PLAYBOOK -o database_file=${sample_name}.sqlite \
+      -o plot_file=${sample_name}.svg track:plot
+  } &
+
+  docker attach sqljs-benchmark-run
+  docker cp sqljs-benchmark-run:/tmp/build/suite-result.json ${sample_name}-result.json
+  docker rm sqljs-benchmark-run
 done

lib/sql-js/benchmark/procpath/karma_docker.procpath

@@ -0,0 +1,28 @@
+# This command may run when "sqljs-benchmark-run" does not yet exist or run
+[renice:watch]
+interval: 2
+repeat: 30
+environment:
+  ROOT_PID=docker inspect -f "{{.State.Pid}}" sqljs-benchmark-run 2> /dev/null || true
+query:
+  PIDS=$..children[?(@.stat.pid in [$ROOT_PID])]..pid
+command:
+  echo $PIDS | tr , '\n' | xargs --no-run-if-empty -I{} -- renice -n -5 -p {}
+
+# Expected input arguments: database_file
+[track:record]
+interval: 1
+stop_without_result: 1
+environment:
+  ROOT_PID=docker inspect -f "{{.State.Pid}}" sqljs-benchmark-run
+query:
+  $..children[?(@.stat.pid == $ROOT_PID)]
+pid_list: $ROOT_PID
+
+# Expected input arguments: database_file, plot_file
+[track:plot]
+moving_average_window: 5
+title: Chromium vs Firefox (№1 RSS, №2 CPU)
+custom_query_file:
+  procpath/top2_rss.sql
+  procpath/top2_cpu.sql

lib/sql-js/benchmark/procpath/top2_cpu.sql

@@ -0,0 +1,29 @@
+WITH diff_all AS (
+    SELECT
+        record_id,
+        ts,
+        stat_pid,
+        stat_utime + stat_stime - LAG(stat_utime + stat_stime) OVER (
+            PARTITION BY stat_pid
+            ORDER BY record_id
+        ) tick_diff,
+        ts - LAG(ts) OVER (
+            PARTITION BY stat_pid
+            ORDER BY record_id
+        ) ts_diff
+    FROM record
+), diff AS (
+    SELECT * FROM diff_all WHERE tick_diff IS NOT NULL
+), one_time_pid_condition AS (
+    SELECT stat_pid
+    FROM record
+    GROUP BY 1
+    ORDER BY SUM(stat_utime + stat_stime) DESC
+    LIMIT 2
+)
+SELECT
+    ts,
+    stat_pid pid,
+    100.0 * tick_diff / (SELECT value FROM meta WHERE key = 'clock_ticks') / ts_diff value
+FROM diff
+JOIN one_time_pid_condition USING(stat_pid)

lib/sql-js/benchmark/procpath/top2_rss.sql

@@ -0,0 +1,13 @@
+WITH one_time_pid_condition AS (
+    SELECT stat_pid
+    FROM record
+    GROUP BY 1
+    ORDER BY MAX(stat_rss) DESC
+    LIMIT 2
+)
+SELECT
+    ts,
+    stat_pid pid,
+    stat_rss / 1024.0 / 1024 * (SELECT value FROM meta WHERE key = 'page_size') value
+FROM record
+JOIN one_time_pid_condition USING(stat_pid)