Metadata-Version: 2.1
Name: thoth-storages
Version: 0.25.13
Summary: Storage and database adapters available in project Thoth
Home-page: https://github.com/thoth-station/storages
Author: Fridolin Pokorny
Author-email: fridolin@redhat.com
Maintainer: Francesco Murdaca
Maintainer-email: fmurdaca@redhat.com
License: GPLv3+
Description: Thoth Storages
        --------------
        
        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.
        
        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 does not provide any CLI, it is rather a low level library
        supporting other parts of Thoth.
        
        You can run prepared test-suite via the following command:
        
        .. code-block:: console
        
          pipenv install --dev
          pipenv run python3 setup.py test
        
          # To generate docs:
          pipenv run python3 setup.py build_sphinx
        
        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 command above, you should be able to access a local
        PostgreSQL instance at ``localhost:5432``. This is also the default
        configuration for PostgreSQL's adapter - you don't need to provide
        ``GRAPH_SERVICE_HOST`` explicitly. 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 for to have an UI for the
        database content. To access it visit `http://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.
        
        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()
        
        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 2 images named ``schema.png`` and
        ``schema_cache.png``. The first PNG file shows schema for the main PostgreSQL
        instance and the latter one, as the name suggests, shows how cache schema looks
        like.
        
        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
        ===================================
        
        You can create your own performance indicators. To create own performance
        indicator, create a script which tests desired functionality of a library. An
        example can be matrix multiplication script present in `performance
        <https://github.com/thoth-station/performance/blob/master/tensorflow/matmul.py>`__
        repository. This script can be supplied to Dependency Monkey to validate
        certain combination of libraries in desired runtime and buildtime environment
        or directly on Amun API which will run the given script using desired software
        and hardware configuration. 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 graph cache and 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 local a fresh
        PostgreSQL instance and fill it from the backup file:
        
        .. code-block:: console
        
          $ cd thoth-station/storages
          $ aws s3 --endpoint <ceph-s3-endpoint> cp s3://<bucket-name>/<prefix>/<deployment-name>/graph-backup/pg_dump-<timestamp> pg_dump-<timestamp>.sql
          $ podman-compose up
          $ psql -h localhost -p 5432 --username=postgres < pg_dump-<timestamp>.sql
          password: <type password "postgres" here>
          <logs will show up>
        
        
        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
          <logs will show up>
          $ psql -h localhost -p 5432 --username=postgres < pg_dump-1569491024.sql
          password: <type password "postgres" here>
          <logs will show up>
        
        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 jobs run in the cluster
        ==========================================
        
        Each job in the cluster reports a JSON which states necessary information about
        the job run (metadata) and actual job results. These results of jobs 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 funcions 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>`__.
        
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