version: 0.2
name: "tdigest_trimmed_mean_1M_samples_comp100"
description: "Benchmarking trimmed mean calculation of a data sketch with 1M elements.
              The T-Digest sketch has a compression of 100.
              The RDB was generated using python as follow:

              import numpy as np
              import redis
              np.random.seed(12345)
              conn = redis.StrictRedis()
              conn.execute_command('TDIGEST.CREATE', 'tdigest', '100')
              for x in np.random.zipf(1.1, size=1000000):
                conn.execute_command('TDIGEST.ADD', 'tdigest', '{}'.format(x), '1.0')
        "
dbconfig:
  - dataset: "https://s3.amazonaws.com/benchmarks.redislabs/redisbloom/datasets/tdigest_1M_samples_compression-50-1000_v2.4.0_dump.rdb"
  - dataset_load_timeout_secs: 180
  - check:
      keyspacelen: 5

clientconfig:
  benchmark_type: "read-only"
  tool: memtier_benchmark
  arguments: "--test-time 180 -c 32 -t 1 --hide-histogram --command 'TDIGEST.TRIMMED_MEAN tdigest:comp:100 0.1 0.9'"
