Difference between revisions of "Meteos/ExampleLinear"
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/sample/data$ head linear_data.txt | /sample/data$ head linear_data.txt | ||
| − | + | 4500,1,1,2016,5,0,40,50 | |
| − | + | 8000,2,1,2016,6,1,60,80 | |
| − | + | 9500,3,1,2016,0,2,88,92 | |
| − | + | 5000,4,1,2016,1,3,90,90 | |
| − | + | 0,5,1,2016,2,2,90,80 | |
| − | + | 4500,6,1,2016,3,3,80,90 | |
| − | + | 4000,7,1,2016,4,1,60,80 | |
| − | + | 4500,8,1,2016,5,0,40,50 | |
| − | + | 8000,9,1,2016,6,0,30,50 | |
| − | + | 9500,10,1,2016,0,0,40,50 | |
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Revision as of 02:30, 8 December 2016
Contents
Predict a Sales Figures using Meteos
In this example, you create a prediction model which predict sales by using Linear Regression.
Linear Regression is one of the algorithms in supervised learning.
1. Create a experiment template
Create template of experiment. Experiment is a workspace of Machine Learning.
You have to confirm a glance image id of meteos image, and a neutron network id before creating a template.
You can use a format located in python-meteosclient/sample/json/template.json
$ glance image-list | grep meteos | 45de4bbd-8419-40ff-8ed7-fc065c05e34f | meteos |
$ neutron net-list | grep public | 84c13e76-ced9-4142-a885-280784f1f7a3 | public | a14de1c5-b8d4-434b-a056-9b0049b93402 |
$ vim sample/json/template.json
$ cat sample/json/template.json
{
"display_name": "example-template",
"display_description": "This is a sample template of experiment",
"image_id" : "45de4bbd-8419-40ff-8ed7-fc065c05e34f",
"master_nodes_num": 1,
"master_flavor_id": "4",
"worker_nodes_num": 2,
"worker_flavor_id": "2",
"spark_version": "1.6.0",
"floating_ip_pool": "84c13e76-ced9-4142-a885-280784f1f7a3"
}
$ meteos template-create --json sample/json/template.json +---------------+-----------------------------------------+ | Property | Value | +---------------+-----------------------------------------+ | cluster_id | None | | created_at | 2016-12-04T07:16:29.000000 | | description | This is a sample template of experiment | | id | 8b7b9b89-f119-4b9b-b9b0-31598f819f1a | | master_flavor | 4 | | master_nodes | 1 | | name | example-template | | project_id | 67401cca74c2409b939e944bc6c8fcbe | | spark_version | 1.6.0 | | status | available | | user_id | 181b1caa9d5b470393ca66b9e511d5b0 | | worker_flavor | 2 | | worker_nodes | 2 | +---------------+-----------------------------------------+
2. Create a experiment from template
Create a experiment by using template created in the above step. You have to confirm a neutron private network id and create keypair before creating a template.
You can use a format located in python-meteosclient/sample/json/experiment.json
$ nova keypair-add key1 > ~/key1.pem && chmod 600 ~/key1.pem
$ neutron net-list | grep private | 8abc626e-2b06-4c67-9b2c-0231f0cef5b8 | private | cb58940f-859b-48c6-b92a-3861470f1fc1 20.0.0.0/26 |
$ vim sample/json/experiment.json
$ cat sample/json/experiment.json
{
"display_name": "example-experiment",
"display_description": "This is a sample experiment",
"key_name": "key1",
"neutron_management_network": "8abc626e-2b06-4c67-9b2c-0231f0cef5b8",
"template_id": "8b7b9b89-f119-4b9b-b9b0-31598f819f1a"
}
$ meteos experiment-create --json sample/json/experiment.json +--------------------+--------------------------------------+ | Property | Value | +--------------------+--------------------------------------+ | created_at | 2016-12-04T07:20:11.000000 | | description | This is a sample experiment | | id | 91504a65-01cf-428f-81aa-596be7ca8619 | | key_name | key1 | | management_network | 8abc626e-2b06-4c67-9b2c-0231f0cef5b8 | | name | example-experiment | | project_id | 67401cca74c2409b939e944bc6c8fcbe | | status | creating | | user_id | 181b1caa9d5b470393ca66b9e511d5b0 | +--------------------+--------------------------------------+
Meteos creates a experiment using OpenStack Sahara spark plugin.
You can see a sahara cluster and nova VMs created by Meteos as below.
$ openstack dataprocessing cluster list (or sahara cluster-list) +------------------+--------------------------------------+-------------+----------------+----------+ | Name | Id | Plugin name | Plugin version | Status | +------------------+--------------------------------------+-------------+----------------+----------+ | cluster-91504a65 | 13418fd9-5d2a-4ee6-b384-cb250b7e7714 | spark | 1.6.0 | Spawning | +------------------+--------------------------------------+-------------+----------------+----------+
$ openstack server list (or nova list) +--------------------------------------+----------------------------+--------+----------+------------+ | ID | Name | Status | Networks | Image Name | +--------------------------------------+----------------------------+--------+----------+------------+ | 58818eb5-ade7-407c-8c76-9fd9809632b4 | cluster-91504a65-workers-1 | BUILD | | meteos | | a151dbd9-de51-43ca-afb8-1fdeecce2891 | cluster-91504a65-workers-0 | BUILD | | meteos | | d02d85c5-0960-4b7e-880c-26b73c5dd8ad | cluster-91504a65-master-0 | BUILD | | meteos | +--------------------------------------+----------------------------+--------+----------+------------+
3. Upload a raw data
Upload a raw data (in this example past sales figures data) to OpenStack Swift.
You can use a sample data located in python-meteosclient/sample/data/linear_data.txt
Raw data shows "sales figures", "day", "month", "year", "day of week", "parameter which indicates weather", "degree", "humidity" from left.
$ cd sample/data/
/sample/data$ head linear_data.txt 4500,1,1,2016,5,0,40,50 8000,2,1,2016,6,1,60,80 9500,3,1,2016,0,2,88,92 5000,4,1,2016,1,3,90,90 0,5,1,2016,2,2,90,80 4500,6,1,2016,3,3,80,90 4000,7,1,2016,4,1,60,80 4500,8,1,2016,5,0,40,50 8000,9,1,2016,6,0,30,50 9500,10,1,2016,0,0,40,50
/sample/data$ swift upload meteos linear_data.txt linear_data.txt
4. Parse a raw data
Parse a raw data to enable Prediction Model to handle it.
You can use a sample format located in python-meteosclient/sample/json/dataset_parse.json
You can see the head data of parsed dataset by executing "meteos dataset-show <dataset-uuid>" command.
$ vim ../python-meteosclient/sample/json/dataset_parse.json
$ cat ../python-meteosclient/sample/json/dataset_parse.json
{
"source_dataset_url": "swift://meteos/linear_data.txt",
"display_name": "sample-data",
"display_description": "user skill dataset",
"method": "parse",
"params": [{"method": "filter", "args": "lambda l: l.split(',')[0] != '0'"}],
"experiment_id": "91504a65-01cf-428f-81aa-596be7ca8619",
"swift_tenant": "demo",
"swift_username": "demo",
"swift_password": "nova"
}
$ meteos dataset-create --json sample/json/dataset_parse.json +-------------+--------------------------------------+ | Property | Value | +-------------+--------------------------------------+ | created_at | 2016-12-08T00:45:43.000000 | | description | This is a sample dataset | | head | None | | id | b6054cab-77b8-4b2d-b6c8-861f69859107 | | name | sample-data | | project_id | 0e3e0f01952948848d8ae438279122fe | | status | creating | | stderr | None | | user_id | 2c3120e8228c4d0e9768f09346fe842d | +-------------+--------------------------------------+
$ meteos dataset-list +--------------------------------------+-------------+--------------------------+-----------+--------------------------------+----------------------------+ | id | name | description | status | source_dataset_url | created_at | +--------------------------------------+-------------+--------------------------+-----------+--------------------------------+----------------------------+ | b6054cab-77b8-4b2d-b6c8-861f69859107 | sample-data | This is a sample dataset | available | swift://meteos/linear_data.txt | 2016-12-08T00:45:43.000000 | +--------------------------------------+-------------+--------------------------+-----------+--------------------------------+----------------------------+
$ meteos dataset-show b6054cab-77b8-4b2d-b6c8-861f69859107 +-------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Property | Value | +-------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | created_at | 2016-12-08T00:45:43.000000 | | description | This is a sample dataset | | head | [u'15000,1,10,2016,6,0,68,50', u'14000,2,10,2016,0,0,68,50', u'5500,3,10,2016,1,1,68,90', u'4500,5,10,2016,3,0,60,55', u'5000,6,10,2016,4,0,60,55', u'4800,7,10,2016,5,2,58,87', u'16000,8,10,2016,6,3,58,60', u'15000,9,10,2016,0,3,60,60', u'3300,10,10,2016,1,2,62,87', u'6000,12,10,2016,3,1,55,93'] | | | | | id | b6054cab-77b8-4b2d-b6c8-861f69859107 | | name | sample-data | | project_id | 0e3e0f01952948848d8ae438279122fe | | status | available | | stderr | | | user_id | 2c3120e8228c4d0e9768f09346fe842d | +-------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
5. Create a prediction model
In this example, User creates a Linear Regression Model from parsed dataset.
Parsed dataset has been already distributed in hdfs of experiment environment.
So, you spefity the internal url (internal://<dataset-id>) in source_dataset_url parameter.
$ vim sample/json/model_linear.json
$ cat sample/json/model_linear.json
{
"display_name": "sample-linear-model",
"display_description": "LinearRegression Model",
"source_dataset_url": "internal://b6054cab-77b8-4b2d-b6c8-861f69859107",
"model_type": "LinearRegression",
"model_params": "{'numIterations': 10}",
"experiment_id": "fad1b912-8f7d-4600-b048-7db27aae1af3"
}
$ meteos model-create --json sample/json/model_linear.json +-------------+-----------------------------------------+ | Property | Value | +-------------+-----------------------------------------+ | created_at | 2016-12-08T00:52:25.000000 | | description | LinearRegression Model | | id | f9b20d78-6f2f-439d-ad71-3db34f3791c9 | | name | sample-linear-model | | params | eydudW1JdGVyYXRpb25zJzogMTB9 | | project_id | 0e3e0f01952948848d8ae438279122fe | | status | creating | | stderr | None | | stdout | None | | type | LinearRegression | | user_id | 2c3120e8228c4d0e9768f09346fe842d | +-------------+-----------------------------------------+
$ meteos model-list +--------------------------------------+---------------------+------------------------+-----------+------------------+-------------------------------------------------+----------------------------+ | id | name | description | status | type | source_dataset_url | created_at | +--------------------------------------+---------------------+------------------------+-----------+------------------+-------------------------------------------------+----------------------------+ | f9b20d78-6f2f-439d-ad71-3db34f3791c9 | sample-linear-model | LinearRegression Model | available | LinearRegression | internal://b6054cab-77b8-4b2d-b6c8-861f69859107 | 2016-12-08T00:52:25.000000 | +--------------------------------------+---------------------+------------------------+-----------+------------------+-------------------------------------------------+----------------------------+
