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mirror of https://github.com/lana-k/sqliteviz.git synced 2025-12-06 18:18:53 +08:00

3 Commits

Author SHA1 Message Date
saaj
9c0103fd05 SQLite 3.41.0 and pearson correlation extension function (#106)
* Build SQLite 3.41.0

* Update pivot_vtab

* Add Pearson correlation coefficient function extension, build

* Add an easy way to running test locally without Nodejs

* Use RSS sum to pick top2 processes for the report

* Try previous Ubuntu LTS as a workaround for Firefox worker not starting
2023-03-04 22:51:25 +01:00
saaj
e4b117ffb9 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
2023-03-04 17:00:46 +01:00
lana-k
3c456ef135 fix sql hint: read properties of undefined #99 2022-07-29 15:27:01 +02:00
18 changed files with 468 additions and 310 deletions

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@@ -11,7 +11,7 @@ on:
jobs:
test:
name: Run tests
runs-on: ubuntu-latest
runs-on: ubuntu-20.04
steps:
- uses: actions/checkout@v2
- name: Use Node.js

24
Dockerfile.test Normal file
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@@ -0,0 +1,24 @@
# An easy way to run tests locally without Nodejs installed:
#
# docker build -t sqliteviz/test -f Dockerfile.test .
#
FROM node:12
RUN set -ex; \
apt update; \
apt install -y chromium firefox-esr; \
npm install -g npm@7
WORKDIR /tmp/build
COPY package.json package-lock.json ./
COPY lib lib
RUN npm install
COPY . .
RUN set -ex; \
sed -i 's/browsers: \[.*\],/browsers: ['"'FirefoxHeadlessTouch'"'],/' karma.conf.js
RUN npm run lint -- --no-fix && npm run test

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@@ -1,4 +1,4 @@
FROM emscripten/emsdk:2.0.24
FROM emscripten/emsdk:3.0.1
WORKDIR /tmp/build

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@@ -43,6 +43,8 @@ SQLite [miscellaneous extensions][3] included:
SQLite 3rd party extensions included:
1. [pivot_vtab][5] -- a pivot virtual table
2. `pearson` correlation coefficient function extension from [sqlean][21]
(which is part of [squib][20])
To ease the step to have working clone locally, the build is committed into
the repository.
@@ -99,3 +101,5 @@ described in [this message from SQLite Forum][12]:
[17]: https://sqlite.org/contrib/
[18]: https://sqlite.org/contrib//download/extension-functions.c?get=25
[19]: https://github.com/lana-k/sqliteviz/blob/master/tests/lib/database/sqliteExtensions.spec.js
[20]: https://github.com/mrwilson/squib/blob/master/pearson.c
[21]: https://github.com/nalgeon/sqlean/blob/incubator/src/pearson.c

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@@ -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/

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@@ -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

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@@ -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

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@@ -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)

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@@ -0,0 +1,13 @@
WITH one_time_pid_condition AS (
SELECT stat_pid
FROM record
GROUP BY 1
ORDER BY SUM(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)

File diff suppressed because one or more lines are too long

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@@ -2,9 +2,11 @@ import logging
import subprocess
from pathlib import Path
# See the setting descriptions on these pages:
# - https://emscripten.org/docs/optimizing/Optimizing-Code.html
# - https://github.com/emscripten-core/emscripten/blob/main/src/settings.js
cflags = (
'-O2',
# SQLite configuration
'-DSQLITE_DEFAULT_CACHE_SIZE=-65536', # 64 MiB
'-DSQLITE_DEFAULT_MEMSTATUS=0',
'-DSQLITE_DEFAULT_SYNCHRONOUS=0',
@@ -13,26 +15,26 @@ cflags = (
'-DSQLITE_ENABLE_FTS3',
'-DSQLITE_ENABLE_FTS3_PARENTHESIS',
'-DSQLITE_ENABLE_FTS5',
'-DSQLITE_ENABLE_JSON1',
'-DSQLITE_ENABLE_NORMALIZE',
'-DSQLITE_EXTRA_INIT=extra_init',
'-DSQLITE_OMIT_DEPRECATED',
'-DSQLITE_OMIT_LOAD_EXTENSION',
'-DSQLITE_OMIT_SHARED_CACHE',
'-DSQLITE_THREADSAFE=0',
# Compile-time optimisation
'-Os', # reduces the code size about in half comparing to -O2
'-flto',
)
emflags = (
# Base
'--memory-init-file', '0',
'-s', 'RESERVED_FUNCTION_POINTERS=64',
'-s', 'ALLOW_TABLE_GROWTH=1',
'-s', 'SINGLE_FILE=0',
# WASM
'-s', 'WASM=1',
'-s', 'ALLOW_MEMORY_GROWTH=1',
# Optimisation
'-s', 'INLINING_LIMIT=50',
'-O3',
'-s', 'ENVIRONMENT=web,worker',
# Link-time optimisation
'-Os',
'-flto',
# sql.js
'-s', 'EXPORTED_FUNCTIONS=@src/sqljs/exported_functions.json',
@@ -50,22 +52,22 @@ def build(src: Path, dst: Path):
'emcc',
*cflags,
'-c', src / 'sqlite3.c',
'-o', out / 'sqlite3.bc',
'-o', out / 'sqlite3.o',
])
logging.info('Building LLVM bitcode for extension-functions.c')
subprocess.check_call([
'emcc',
*cflags,
'-c', src / 'extension-functions.c',
'-o', out / 'extension-functions.bc',
'-o', out / 'extension-functions.o',
])
logging.info('Building WASM from bitcode')
subprocess.check_call([
'emcc',
*emflags,
out / 'sqlite3.bc',
out / 'extension-functions.bc',
out / 'sqlite3.o',
out / 'extension-functions.o',
'-o', out / 'sql-wasm.js',
])

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@@ -8,7 +8,7 @@ from pathlib import Path
from urllib import request
amalgamation_url = 'https://sqlite.org/2022/sqlite-amalgamation-3390000.zip'
amalgamation_url = 'https://sqlite.org/2023/sqlite-amalgamation-3410000.zip'
# Extension-functions
# ===================
@@ -28,10 +28,11 @@ extension_urls = (
('https://sqlite.org/src/raw/09f967dc?at=decimal.c', 'sqlite3_decimal_init'),
# Third-party extension
# =====================
('https://github.com/jakethaw/pivot_vtab/raw/08ab0797/pivot_vtab.c', 'sqlite3_pivotvtab_init'),
('https://github.com/jakethaw/pivot_vtab/raw/9323ef93/pivot_vtab.c', 'sqlite3_pivotvtab_init'),
('https://github.com/nalgeon/sqlean/raw/95e8d21a/src/pearson.c', 'sqlite3_pearson_init'),
)
sqljs_url = 'https://github.com/sql-js/sql.js/archive/refs/tags/v1.5.0.zip'
sqljs_url = 'https://github.com/sql-js/sql.js/archive/refs/tags/v1.7.0.zip'
def _generate_extra_init_c_function(init_function_names):

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@@ -1,6 +1,6 @@
{
"name": "sqliteviz",
"version": "0.21.0",
"version": "0.21.1",
"license": "Apache-2.0",
"private": true,
"scripts": {

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@@ -3,14 +3,20 @@ import 'codemirror/addon/hint/show-hint.js'
import 'codemirror/addon/hint/sql-hint.js'
import store from '@/store'
function _getHintText (hint) {
return typeof hint === 'string' ? hint : hint.text
}
export function getHints (cm, options) {
const token = cm.getTokenAt(cm.getCursor()).string.toUpperCase()
const result = CM.hint.sql(cm, options)
// Don't show the hint if there is only one option
// and the token is already completed with this option
if (result.list.length === 1 && result.list[0].text.toUpperCase() === token) {
// and the replacingText is already equals to this option
const replacedText = cm.getRange(result.from, result.to).toUpperCase()
if (result.list.length === 1 &&
_getHintText(result.list[0]).toUpperCase() === replacedText) {
result.list = []
}
return result
}

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@@ -293,7 +293,7 @@ describe('SQLite extensions', function () {
it('supports decimal', async function () {
const actual = await db.execute(`
select
SELECT
decimal_add(decimal('0.1'), decimal('0.2')) "add",
decimal_sub(0.2, 0.1) sub,
decimal_mul(power(2, 69), 2) mul,
@@ -430,4 +430,29 @@ describe('SQLite extensions', function () {
]
})
})
it('supports pearson', async function () {
const actual = await db.execute(`
CREATE TABLE dataset(x REAL, y REAL, z REAL);
INSERT INTO dataset VALUES
(5,3,3.2), (5,6,4.3), (5,9,5.4),
(10,3,4), (10,6,3.8), (10,9,3.6),
(15,3,4.8), (15,6,4), (15,9,3.5);
SELECT
pearson(x, x) xx,
pearson(x, y) xy,
abs(-0.12666 - pearson(x, z)) < 0.00001 xz,
pearson(y, x) yx,
pearson(y, y) yy,
abs(0.10555 - pearson(y, z)) < 0.00001 yz,
abs(-0.12666 - pearson(z, x)) < 0.00001 zx,
abs(0.10555 - pearson(z, y)) < 0.00001 zy,
pearson(z, z) zz
FROM dataset;
`)
expect(actual.values).to.eql({
xx: [1], xy: [0], xz: [1], yx: [0], yy: [1], yz: [1], zx: [1], zy: [1], zz: [1]
})
})
})

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@@ -138,15 +138,37 @@ describe('hint.js', () => {
'getHints returns [ ] if there is only one option and token is completed with this option',
() => {
// mock CM.hint.sql and editor
sinon.stub(CM.hint, 'sql').returns({ list: [{ text: 'SELECT' }] })
sinon.stub(CM.hint, 'sql').returns({
list: [{ text: 'SELECT' }],
from: null, // from/to doesn't metter because getRange is mocked
to: null
})
const editor = {
getTokenAt () {
return {
string: 'select',
type: 'keyword'
getRange () {
return 'select'
}
}
const hints = getHints(editor, {})
expect(hints.list).to.eql([])
}
)
it(
'getHints returns [ ] if there is only one string option and token ' +
'is completed with this option',
() => {
// mock CM.hint.sql and editor
sinon.stub(CM.hint, 'sql').returns({
list: ['house.name'],
from: null, // from/to doesn't metter because getRange is mocked
to: null
})
const editor = {
getRange () {
return 'house.name'
}
},
getCursor: sinon.stub()
}
const hints = getHints(editor, {})
@@ -160,15 +182,11 @@ describe('hint.js', () => {
{ text: 'SELECT' },
{ text: 'ST' }
]
sinon.stub(CM.hint, 'sql').returns({ list })
sinon.stub(CM.hint, 'sql').returns({ list, from: null, to: null })
const editor = {
getTokenAt () {
return {
string: 'se',
type: 'keyword'
getRange () {
return 'se'
}
},
getCursor: sinon.stub()
}
const hints = getHints(editor, {})
@@ -182,15 +200,11 @@ describe('hint.js', () => {
() => {
// mock CM.hint.sql and editor
const list = [{ text: 'SELECT' }]
sinon.stub(CM.hint, 'sql').returns({ list })
sinon.stub(CM.hint, 'sql').returns({ list, from: null, to: null })
const editor = {
getTokenAt () {
return {
string: 'sele',
type: 'keyword'
getRange () {
return 'sele'
}
},
getCursor: sinon.stub()
}
const hints = getHints(editor, {})