Because everybody loves test data.
es_test_data.py
lets you generate and upload randomized test data to your ES cluster so you can start running queries, see what performance is like, and verify your cluster is able to handle the load.
It allows for easy configuring of what the test documents look like, what kind of data types they include and what the field names are called.
Let's assume you have an Elasticsearch cluster running. If not, set it up locally and point your browser to http://localhost:9200 to see if it's up.
Python and Tornado are used, run pip install tornado
to install Tornado if you don't have it already.
It's as simple as this:
$ python es_test_data.py --es_url=http://localhost:9200
[I 150604 15:43:19 es_test_data:42] Trying to create index http://localhost:9200/test_data
[I 150604 15:43:19 es_test_data:47] Guess the index exists already
[I 150604 15:43:19 es_test_data:184] Generating 10000 docs, upload batch size is 1000
[I 150604 15:43:19 es_test_data:62] Upload: OK - upload took: 25ms, total docs uploaded: 1000
[I 150604 15:43:20 es_test_data:62] Upload: OK - upload took: 25ms, total docs uploaded: 2000
[I 150604 15:43:20 es_test_data:62] Upload: OK - upload took: 19ms, total docs uploaded: 3000
[I 150604 15:43:20 es_test_data:62] Upload: OK - upload took: 18ms, total docs uploaded: 4000
[I 150604 15:43:20 es_test_data:62] Upload: OK - upload took: 27ms, total docs uploaded: 5000
[I 150604 15:43:20 es_test_data:62] Upload: OK - upload took: 19ms, total docs uploaded: 6000
[I 150604 15:43:20 es_test_data:62] Upload: OK - upload took: 15ms, total docs uploaded: 7000
[I 150604 15:43:20 es_test_data:62] Upload: OK - upload took: 24ms, total docs uploaded: 8000
[I 150604 15:43:20 es_test_data:62] Upload: OK - upload took: 32ms, total docs uploaded: 9000
[I 150604 15:43:20 es_test_data:62] Upload: OK - upload took: 31ms, total docs uploaded: 10000
[I 150604 15:43:20 es_test_data:216] Done - total docs uploaded: 10000, took 1 seconds
[I 150604 15:43:20 es_test_data:217] Bulk upload average: 23 ms
[I 150604 15:43:20 es_test_data:218] Bulk upload median: 24 ms
[I 150604 15:43:20 es_test_data:219] Bulk upload 95th percentile: 31 ms
$
Without any command line options, it will generate and upload 1000 documents of the format
{
"name":<<str>>,
"age":<<int>>,
"last_updated":<<ts>>
}
to an Elasticsearch cluster at http://localhost:9200
to an index called test_data
.
python es_test_data.py --help
gives you the full set of command line options, here are the most important ones:
--es_url=http://localhost:9200
the base URL of your ES node, don't include the index name--count=###
number of documents to generate and upload--index_name=test_data
the name of the index to upload the data to. If it doesn't exist it'll be created with these options--num_of_shards=2
the number of shards for the indexnum_of_replicas=0
the number of replicas for the index
--batch_size=###
we use bulk upload to send the docs to ES, this option controls how many we send at a time--force_init_index=False
ifTrue
it will delete and re-create the index--dict_file=filename.dic
if provided thedict
data type will use words from the dictionary file, format is one word per line. The entire file is loaded at start-up so be careful with (very) large files. You can download wordlists e.g.. from here.
Glad you're asking, let's get to the doc format.
The doc format is configured via --format=<<FORMAT>>
with the default being name:str,age:int,last_updated:ts
.
The general syntax looks like this:
<<field_name>>:<<field_type>>,<<field_name>>::<<field_type>>, ...
For every document, es_test_data.py
will generate random values for each of the fields configured.
Currently supported field types are:
ts
a timestamp (in milliseconds), randomly picked between now +/- 30 daysint:min:max
a random integer betweenmin
andmax
. Ifmin and
max` are not provided they default to 0 and 100000str:min:max
a word ( as in, a string), made up ofmin
tomax
random upper/lowercase and digit characters. Ifmin
andmax
are optional, defaulting to3
and10
words:min:max
a random number ofstrs
, separated by space,min
andmax
are optional, defaulting to '2' and10
dict:min:max
a random number of entries from the dictionary file, separated by space,min
andmax
are optional, defaulting to '2' and10
- document the remaining cmd line options
- more different format types
- ...
All suggestions, comments, ideas, pull requests are welcome!