The JavaScript Database, for Node.js, nw.js, electron and the browser
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nedb/benchmarks/insert.js

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1.7 KiB

var Datastore = require('../lib/datastore')
, benchDb = 'workspace/insert.bench.db'
, async = require('async')
, commonUtilities = require('./commonUtilities')
, execTime = require('exec-time')
, profiler = new execTime('INSERT BENCH')
, d
, program = require('commander')
, n
;
program
.option('-n --number [number]', 'Size of the collection to test on', parseInt)
.option('-i --with-index', 'Use an index')
.option('-p --with-pipeline', 'Use pipelining')
.parse(process.argv);
n = program.number || 10000;
console.log("----------------------------");
console.log("Test with " + n + " documents");
console.log(program.withIndex ? "Use an index" : "Don't use an index");
console.log(program.withPipeline ? "Use an pipelining" : "Don't use pipelining");
console.log("----------------------------");
d = new Datastore({ filename: benchDb, pipeline: program.withPipeline });
async.waterfall([
async.apply(commonUtilities.prepareDb, benchDb)
, function (cb) {
d.loadDatabase(function (err) {
if (err) { return cb(err); }
if (program.withIndex) {
d.ensureIndex({ fieldName: 'docNumber' });
n = 2 * n; // We will actually insert twice as many documents
// because the index is slower when the collection is already
// big. So the result given by the algorithm will be a bit worse than
// actual performance
}
cb();
});
}
, function (cb) { profiler.beginProfiling(); return cb(); }
, async.apply(commonUtilities.insertDocs, d, n, profiler)
], function (err) {
profiler.step("Benchmark finished");
if (err) { return console.log("An error was encountered: ", err); }
});