Thoth Storages
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This library provides a library called thoth-storages <https://pypi.org/project/thoth-storages>
__ used in project Thoth <https://thoth-station.ninja>
. The library exposes core queries and methods
for PostgreSQL database <https://www.postgresql.org/>
as well as adapters
for manipulating with Ceph <https://ceph.io/>
__ via its S3 compatible API.
Quick Start
Pre-requisites:
- make sure you have
podman
and podman-compose
installed. You can install those tools by running dnf install -y podman podman-compose
- make sure you are in an environment created with
pipenv install --dev
To develop locally the first time:
Now you are ready to test new queries or create new migrations <https://github.com/thoth-station/storages#generating-migrations-and-schema-adjustment-in-deployment>
__
If you already have a local database, make sure it is not outdated and rember to follow the Generating migrations and schema adjustment in deployment <https://github.com/thoth-station/storages#generating-migrations-and-schema-adjustment-in-deployment>
__
section before testing any changes.
Installation and Usage
The library can be installed via pip or Pipenv from PyPI <https://pypi.org/project/thoth-storages>
__:
.. code-block:: console
pipenv install thoth-storages
The library provides a CLI that can assist you with exploring schema and data
storing:
.. code-block:: console
thoth-storages --help
In a cloned repo, run:
PYTHONPATH=. pipenv run python3 thoth-storages --help
You can run prepared test-suite via the following command:
.. code-block:: console
pipenv install --dev
pipenv run python3 setup.py test
Running PostgreSQL locally
You can use docker-compose.yaml
present in this repository to run a local
PostgreSQL instance, (make sure you installed podman-compose <https://github.com/containers/podman-compose>
__):
.. code-block:: console
$ dnf install -y podman podman-compose
$ # Also available from PyPI: pip install podman-compose
$ podman-compose up
After running the commands above, you should be able to access a local
PostgreSQL instance at localhost:5432 <http://localhost:5432>
__. This is also
the default configuration for PostgreSQL's adapter that connects to localhost
unless KNOWLEDGE_GRAPH_HOST
is supplied explicitly (see also other
environment variables in the adapter constructor for more info on configuring
the connection). The default configuration uses database named postgres
which can be accessed using postgres
user and postgres
password (SSL is
disabled).
The provided docker-compose.yaml
has also PGweb <https://sosedoff.github.io/pgweb/>
__ enabled to enable data exploration using
UI. To access it visit localhost:8081 <http://localhost:8081>
__.
The provided docker-compose.yaml
does not use any volume. After you
containers restart, the content will not be available anymore.
You can sync your local instance using pgsql
:
.. code-block:: console
$ psql -h localhost -p 5432 --username=postgres < pg_dump.sql
If you would like to experiment with PostgreSQL programmatically, you can use
the following code snippet as a starting point:
.. code-block:: python
from thoth.storages import GraphDatabase
graph = GraphDatabase()
graph.connect()
To clear database:
graph.drop_all()
To initialize schema in the graph database:
graph.initialize_schema()
Generating migrations and schema adjustment in deployment
If you make any changes to data model of the main PostgreSQL database, you need
to generate migrations. These migrations state how to adjust already existing
database with data in deployments. For this purpose, Alembic migrations <https://alembic.sqlalchemy.org>
__ are used. Alembic can (partially <https://alembic.sqlalchemy.org/en/latest/autogenerate.html#what-does-autogenerate-detect-and-what-does-it-not-detect>
__)
automatically detect what has changed and how to adjust already existing
database in a deployment.
Alembic uses incremental version control, where each migration is versioned and
states how to migrate from previous state of database to the desired next state
- these versions are present in
alembic/versions
directory and are
automatically generated with procedure described bellow.
If you make any changes, follow the following steps which will generate version
for you:
-
Make sure your local PostgreSQL instance is running (follow Running PostgreSQL locally
instructions above):
.. code-block:: console
$ podman-compose up
-
Run Alembic CLI to generate versions for you:
.. code-block:: console
Make sure you have your environment setup:
pipenv install --dev
Make sure you are running the most recent version of schema:
$ PYTHONPATH=. pipenv run alembic upgrade head
Actually generate a new version:
$ PYTHONPATH=. pipenv run alembic revision --autogenerate -m "Added row to calculate sum of sums which will be divided by 42"
-
Review migrations generated by Alembic. Note NOT all changes are automatically detected by Alembic <https://alembic.sqlalchemy.org/en/latest/autogenerate.html#what-does-autogenerate-detect-and-what-does-it-not-detect>
__.
-
Make sure generated migrations are part of your pull request so changes are
propagated to deployments:
.. code-block:: console
$ git add thoth/storages/data/alembic/versions/
-
In a deployment, use Management API and its /graph/initialize
endpoint to
propagate database schema changes in deployment (Management API has to have
recent schema changes present which are populated with new thoth-storages
releases).
-
If running locally and you would like to propagate changes, run the following
Alembic command to update migrations to the latest version:
.. code-block:: console
$ PYTHONPATH=. pipenv run alembic upgrade head
If you would like to update schema programmatically run the following Python
code:
.. code-block:: python
from thoth.storages import GraphDatabase
graph = GraphDatabase()
graph.connect()
graph.initilize_schema()
When updating a deployment, make sure all the components use the same database
schema. Metrics exposed from a deployment should state schema version of all
the components in a deployment.
Generate schema images
You can use shipped CLI thoth-storages
to automatically generate schema
images out of the current models:
.. code-block:: console
First, make sure you have dev packages installed:
$ pipenv install --dev
$ PYTHONPATH=. pipenv run python3 ./thoth-storages generate-schema
The command above will produce an image named schema.png
. Check --help
to get more info on available options.
If the command above fails with the following exception:
.. code-block:: console
FileNotFoundError: [Errno 2] "dot" not found in path.
make sure you have graphviz
package installed:
.. code-block:: console
dnf install -y graphviz
Creating own performance indicators
Performance indicators report performance aspect of a library on Amun <https://github.com/thoth-station/amun-api>
__ and results can be automatically
synced if the following procedure is respected.
To create own performance
indicator, create a script which tests desired functionality of a library. An
example can be matrix multiplication script present in thoth-station/performance <https://github.com/thoth-station/performance/blob/master/tensorflow/matmul.py>
__
repository. This script can be supplied to Dependency Monkey <https://thoth-station.ninja/docs/developers/adviser/dependency_monkey.html>
__
to validate certain combination of libraries in desired runtime and buildtime
environment. Please follow instructions on how to create a performance script
shown in the README of performance repo <https://github.com/thoth-station/performance>
__.
To create relevant models, adjust
thoth/storages/graph/models_performance.py
file and add your model.
Describe parameters (reported in @parameters
section of performance
indicator result) and result (reported in @result
). The name of class
should match name
which is reported by performance indicator run.
.. code-block:: python
class PiMatmul(Base, BaseExtension, PerformanceIndicatorBase):
"""A class for representing a matrix multiplication micro-performance test."""
# Device used during performance indicator run - CPU/GPU/TPU/...
device = Column(String(128), nullable=False)
matrix_size = Column(Integer, nullable=False)
dtype = Column(String(128), nullable=False)
reps = Column(Integer, nullable=False)
elapsed = Column(Float, nullable=False)
rate = Column(Float, nullable=False)
All the models use SQLAchemy <https://www.sqlalchemy.org/>
. See docs <https://docs.sqlalchemy.org/>
for more info.
Online debugging of queries
You can print to logger all the queries that are performed to a PostgreSQL
instance. To do so, set the following environment variable:
.. code-block:: console
export THOTH_STORAGES_DEBUG_QUERIES=1
Memory usage statisticts
You can print information about PostgreSQL adapter together with statistics on
the adapter in-memory cache usage to logger (it has to have at least level
INFO
set). To do so, set the following environment variable:
.. code-block:: console
export THOTH_STORAGES_LOG_STATS=1
These statistics will be printed once the database adapter is destructed.
Automatic backups of Thoth deployment
In each deployment, an automatic knowledge graph backup cronjob <https://github.com/thoth-station/graph-backup-job>
__ is run, usually once a
day. Results of automatic backups are stored on Ceph - you can find them in
s3://<bucket-name>/<prefix>/<deployment-name>/graph-backup/pg_dump-<timestamp>.sql
.
Refer to deployment configuration for expansion of parameters in the path.
To create a database instance out of this backup file, run a fresh local
PostgreSQL instance and fill it from the backup file:
.. code-block:: console
$ cd thoth-station/storages
$ aws s3 --endpoint cp s3://///graph-backup/pg_dump- pg_dump-.sql
$ podman-compose up
$ psql -h localhost -p 5432 --username=postgres < pg_dump-.sql
password: <type password "postgres" here>
Manual backups of Thoth deployment
You can use pg_dump
and psql
utilities to create dumps and restore the
database content from dumps. This tool is pre-installed in the container image
which is running PostgreSQL so the only thing you need to do is execute
pg_dump
in Thoth's deployment in a PostgreSQL container to create a dump,
use oc cp
to retrieve dump (or directly use oc exec
and create the dump
from the cluster) and subsequently psql
to restore the database content.
The prerequisite for this is to have access to the running container (edit
rights).
.. code-block:: console
Execute the following commands from the root of this Git repo:
List PostgreSQL pods running:
$ oc get pod -l name=postgresql
NAME READY STATUS RESTARTS AGE
postgresql-1-glwnr 1/1 Running 0 3d
Open remote shell to the running container in the PostgreSQL pod:
$ oc rsh -t postgresql-1-glwnr bash
Perform dump of the database:
(cluster-postgres) $ pg_dump > pg_dump-$(date +"%s").sql
(cluster-postgres) $ ls pg_dump-*.sql # Remember the current dump name
(cluster-postgres) pg_dump-1569491024.sql
(cluster-postgres) $ exit
Copy the dump to the current dir:
$ oc cp thoth-test-core/postgresql-1-glwnr:/opt/app-root/src/pg_dump-1569491024.sql .
Start local PostgreSQL instance:
$ podman-compose up --detach
$ psql -h localhost -p 5432 --username=postgres < pg_dump-1569491024.sql
password: <type password "postgres" here>
You can ignore error messages related to an owner error like this:
.. code-block:: console
STATEMENT: ALTER TABLE public.python_software_stack OWNER TO thoth;
ERROR: role "thoth" does not exist
The PostgreSQL container uses user "postgres" by default which is different
from the one run in the cluster ("thoth"). The role assignment will simply not
be created but data will be available.
Syncing results of a workflow run in the cluster
Each workflow task in the cluster reports a JSON which states necessary
information about the task run (metadata) and actual results. These results of
workflow tasks are stored on object storage Ceph <https://ceph.io/>
__ via S3
compatible API and later on synced via graph syncs to the knowledge graph. The
component responsible for graph syncs is graph-sync-job <https://github.com/thoth-station/graph-sync-job>
__ which is written generic
enough to sync any data and report metrics about synced data so you don't need
to provide such logic on each new workload registered in the system. To sync
your own results of job results (workload) done in the cluster, implement
related syncing logic in the sync.py <https://github.com/thoth-station/storages/blob/master/thoth/storages/sync.py>
__
and register handler in the HANDLERS_MAPPING
in the same file. The mapping
maps prefix of the document id to the handler (function) which is responsible
for syncing data into the knowledge base (please mind signatures of existing
syncing functions to automatically integrate with sync_documents
function
which is called from graph-sync-job
).
Query Naming conventions in Thoth
For query naming conventions, please read all the docs in conventions for query name <https://github.com/thoth-station/storages/blob/master/docs/conventions/README.md>
__.
Accessing data on Ceph
To access data on Ceph, you need to know aws_access_key_id
and aws_secret_access_key
credentials
of endpoint you are connecting to.
Absolute file path of data you are accessing is constructed as: s3://<bucket_name>/<prefix_name>/<file_path>
There are two ways to initialize the data handler:
-
Configure environment variables
.. list-table::
:widths: 25 25
:header-rows: 1
-
-
S3_ENDPOINT_URL
- Ceph Host name
-
CEPH_BUCKET
- Ceph Bucket name
-
CEPH_BUCKET_PREFIX
- Ceph Prefix
-
-
CEPH_SECRET_KEY
- Ceph Secret Key
.. code-block:: python
from thoth.storages.ceph import CephStore
ceph = CephStore()
-
Initialize the object directly with parameters
.. code-block:: python
from thoth.storages.ceph import CephStore
ceph = CephStore(
key_id=<aws_access_key_id>,
secret_key=<aws_secret_access_key>,
prefix=<prefix_name>,
host=<endpoint_url>,
bucket=<bucket_name>)
After initialization, you are ready to retrieve data
.. code-block:: python
ceph.connect()
try:
# For dictionary stored as json
json_data = ceph.retrieve_document(<file_path>)
# For general blob
blob = ceph.retrieve_blob(<file_path>)
except NotFoundError:
# File does not exist
Accessing Thoth Data on the Operate-First Public Bucket
A public instance of Thoth's database is available on the Operate-First Public Bucket <https://github.com/operate-first/apps/blob/master/docs/content/odh/trino/access_public_bucket.md>
__ for external contributors to start developing components of Thoth.
Instructions for accessing the bucket are available in the documentation <https://github.com/thoth-station/datasets#accessing-thoth-data-on-the-operate-first-public-bucket>
__ of the thoth/datasets <https://github.com/thoth-station/datasets>
__ repository.
Be careful not to store any confidential or valuable information in this bucket as its content can be wiped out at any time.