/TS-Benchmark

时序基准评测工具

Primary LanguageJupyter NotebookGNU General Public License v3.0GPL-3.0

TS-Benchmark

Description

This project is the source code of TS-Benchmark.

Start

The general steps to complete the test are:

  1. Data generation cd data_generation

  2. Train DCGAN model python DCGAN.py Run the encoder_dc.py file to train the encoder, python encoder_dc.py Finally execute the test python test_dc.py

  3. Data Import Since each database have different build-in tools for data import, we have defined some tools related to data import in the tsdb-test/data/load directory

  4. build project cd Tsdb-benchmark/ts-benchmark/ sh build.sh

  5. config parametes of database and run the benchmark cd Tsdb-benchmark/ts-benchmark/ vim run.sh (choose database and test mode) sh run.sh

Params description

The configuration of TSDBs is shown as follows:

  • InfluxDB. We enlarge the default values of some important parameters of the TSM engine for better performance of the system. For example, the parameter wal-fsync- delay is set as "0s", the parameter cache-max-memory-size is set to 1,048,576,000 bytes, and the parameter cache-snapshot-memory-size is enlarged to “100M” and so on. Maximum memory size is sufficient. The parameter max-values-per-tag is set as 0 to allow an unlimited number of tag values.
  • TimescaleDB. The parameter shared-buffers is set as 8GB, maintenance-work-mem is set as 2GB, checkpoint-completion-target is set as 0.7, min_wal size is set as 1GB, and max wal size is 2GB. Parameters of PostgreSQL is set based on PgTune.
  • Druid. The parameter Roll-up is set as true, and Granu-larity is set as hour. For local batch import, the parameter maxRowsPerSegment is set as 10M, maxRowsInMemory is set as 20M, and maxTotalRows is set as 100M.
  • OpenTSDB. The parameter tsd-http-request-enable-chunked is enabled, tsd-http-request-max-chunk is set as 32KB, tsd-core-auto-create-metrics is set as true, and the parameter tsd-storage-enable-compaction is set to be false to improve the write performance.

More

If you have interests in the directed graph construction and the generation via random walk. you can ref to the random_walk.ipynb Quick Open It!

More information please ref to for detail