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Optional tools and utilities for pmemkv
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README.md

pmemkv-tools

Optional tools and utilities for pmemkv

This is experimental pre-release software and should not be used in production systems. APIs and file formats may change at any time without preserving backwards compatibility. All known issues and limitations are logged as GitHub issues.

LD_LIBRARY_PATH

When running on Fedora, force the library path like this:

export LD_LIBRARY_PATH=/usr/local/lib:/usr/local/lib64

Benchmarking

The pmemkv_bench utility provides some standard read & write benchmarks. This is based on the db_bench utility included with LevelDB and RocksDB, although the list of supported parameters is slightly different.

To build pmemkv_bench:

make bench

Supported runtime parameters:

--engine=<name>            (storage engine name, default: cmap)
--db=<location>            (path to persistent pool, default: /dev/shm/pmemkv)
                           (note: file on DAX filesystem, DAX device, or poolset file)
--db_size_in_gb=<integer>  (size of persistent pool to create in GB, default: 0)
                           (note: always use 0 with poolset or device DAX configs)
--histogram=<0|1>          (show histograms when reporting latencies)
--num=<integer>            (number of keys to place in database, default: 1000000)
--reads=<integer>          (number of read operations, default: 1000000)
--threads=<integer>        (number of concurrent threads, default: 1)
--value_size=<integer>     (size of values in bytes, default: 100)
--benchmarks=<name>,       (comma-separated list of benchmarks to run)
    fillseq                (load N values in sequential key order)
    fillrandom             (load N values in random key order)
    overwrite              (replace N values in random key order)
    readseq                (read N values in sequential key order)
    readrandom             (read N values in random key order)
    readmissing            (read N missing values in random key order)
    deleteseq              (delete N values in sequential key order)
    deleterandom           (delete N values in random key order)
    readwhilewriting       (1 writer, N threads doing random reads)
    readrandomwriterandom  (N threads doing random-read, random-write)

Benchmarking on emulated persistent memory:

PMEM_IS_PMEM_FORCE=1 ./pmemkv_bench --db=/dev/shm/pmemkv --db_size_in_gb=1

Benchmarking on filesystem DAX:

./pmemkv_bench --db=/mnt/pmem/pmemkv --db_size_in_gb=1

Benchmarking on device DAX:

./pmemkv_bench --db=/dev/dax1.0

Benchmarking with poolset:

./pmemkv_bench --db=~/pmemkv.poolset

Baselines

Baseline tests are simple single-threaded tests that compare average per-operation latency between different language bindings and the blackhole engine. These are used to analyze and improve performance of our language bindings.

Some of baselines, examples and other programs/scripts may use tree3 engine, which is not enabled in pmemkv by default. You have to enable it using CMake option: cmake .. -DENGINE_TREE3=ON. For more details see pmemkv/INSTALLING.md.

make baseline_c
make baseline_cpp
make baseline_java
make baseline_nodejs
make baseline_ruby
make baseline_python

Examples

Examples are in individual repos:

Iteration

These measure iteration performance against a dataset with 100M keys. (15GB total)

make iteration_cpp
make iteration_java
make iteration_python

Storage Efficiency

This script reports the storage efficiency for different engines and value sizes.

make storage_efficiency
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