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.. _faq: | ||
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Frequently Asked Questions | ||
========================== | ||
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General | ||
------- | ||
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What is this project? | ||
~~~~~~~~~~~~~~~~~~~~~~ | ||
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linkml-store is a data management solution that provides a common interface to multiple backends, | ||
including DuckDB, MongoDB, Neo4J, and Solr. | ||
It is designed to make it easier to work with data in different forms (tabular, JSON, columnar, RDF), | ||
provide expressive validation at scale, and enable the ability to mix and match different backends. | ||
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Is this a database engine? | ||
~~~~~~~~~~~~~~~~~~~~~~~~~~ | ||
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No, linkml-store is not a database engine in itself. It is designed to be used *in combination* | ||
with your favorite database engines. | ||
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Do I need to know LinkML to use this? | ||
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | ||
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No, you do not need to know LinkML to use linkml-store. In fact you can use linkml-store in | ||
"YOLO mode" where you don't even specify a schema (a schema will be induced as far as possible). | ||
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However, for serious applications we recommend you always provide a LinkML schema for your | ||
different datasets. | ||
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For more information on LinkML, see the `LinkML documentation <https://linkml.io/linkml/>`_. | ||
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Can I use the command line? | ||
~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | ||
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Yes, linkml-store provides a command line interface. | ||
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See the `Command Line Tutorial <https://linkml.io/linkml-store/tutorials/Command-Line-Tutorial.html>`_ for examples. | ||
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All commands can be used via the base ``linkml-store`` command: | ||
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.. code-block:: bash | ||
linkml-store --help | ||
Note some command line options may change in future until this package is 1.0.0 | ||
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Can I use the Python API? | ||
~~~~~~~~~~~~~~~~~~~~~~~~~ | ||
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Yes, linkml-store provides a Python API. | ||
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See the `Python Tutorial <https://linkml.io/linkml-store/tutorials/Python-Tutorial.html>`_ for examples. | ||
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Example: | ||
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.. code-block:: python | ||
from linkml_store import Client | ||
client = Client() | ||
db = client.attach_database("duckdb") | ||
collection = db.attach_collection("my_collection") | ||
collection.insert({"name": "Alice", "age": 42}) | ||
result = collection.find({"name": "Alice"}) | ||
Can I use a web API? | ||
~~~~~~~~~~~~~~~~~~~~ | ||
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Yes, you can stand up a web API. | ||
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To start you should first create a config file, e.g. ``db/conf.yaml``: | ||
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Then run: | ||
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.. code-block:: bash | ||
export LINKML_STORE_CONFIG=./db/conf.yaml | ||
make api | ||
Can I use a web UI? | ||
~~~~~~~~~~~~~~~~~~~~ | ||
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We provide a *very rudimentary* web UI. To start you should first create a config file, e.g. ``db/conf.yaml``: | ||
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Then run: | ||
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.. code-block:: bash | ||
export LINKML_STORE_CONFIG=./db/conf.yaml | ||
make app | ||
What is CRUDSI? | ||
~~~~~~~~~~~~~~~ | ||
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CRUDSI is our not particularly serious name for the design pattern that linkml-store follows. | ||
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Many database engines and database solutions implement a CRUD layer: | ||
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* Create | ||
* Read | ||
* Update | ||
* Delete | ||
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linkml-store adds two more operations: | ||
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* Search | ||
* Inference | ||
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Is this an AI/Machine Learning/LLM/Vector database platform? | ||
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | ||
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linkml-store is first and foremost a *data management* platform. However, | ||
we do provide optional integrations to AI and ML tooling. In particular, you can plug and | ||
play different solutions for implementing search indexes, including LLM textual embeddings. | ||
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Additionally, we believe that robust data management using rich and expressive semantic | ||
schemas (in combination with the database engine of your choice) is the key to | ||
making data **AI-ready**. | ||
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Is linkml-store production ready? | ||
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | ||
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linkml-store is currently not as mature as the core LinkML products. Be warned that | ||
the API and command line options may change. However, things may be moving fast, | ||
and you are invited to check back in here later! | ||
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Are there tutorials? | ||
~~~~~~~~~~~~~~~~~~~~ | ||
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See :ref:`tutorials` | ||
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Installation | ||
------- | ||
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How do I install linkml-store? | ||
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | ||
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.. code-block:: bash | ||
pip install "linkml-store[all]" | ||
This installs both necessary and optional dependencies. We recommend this for now. | ||
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As a developer, how do I install linkml-store? | ||
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | ||
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Check out the repo, and like all linkml projects, use Poetry: | ||
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.. code-block:: bash | ||
git clone <URL> | ||
cd linkml-store | ||
make install | ||
Backend Integrations | ||
------------ | ||
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Does linkml-store support DuckDB? | ||
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | ||
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Yes, linkml-store supports DuckDB as a backend. DuckDB is a modern columnar in-memory database | ||
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See the :ref:`tutorial <tutorials>` for examples. | ||
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Note that currently for DuckDB we bypass the `standard linkml to SQL to relational mapping <https://linkml.io/linkml/generators/sqltable.html>`_ step, | ||
and instead use DuckDB more like a data frame store. Nested objects and lists are stored directly | ||
(using DuckDB's json integrations behind the scenes), rather than fully normalized. | ||
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Does linkml-store support MongoDB? | ||
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | ||
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Yes, linkml-store supports MongoDB as a backend. MongoDB is a popular NoSQL database. | ||
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See the `MongoDB how-to guide <https://linkml.io/linkml-store/how-to/Use-MongoDB.html>`_ for examples. | ||
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Does linkml-store support Neo4J? | ||
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | ||
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Yes, linkml-store supports Neo4J as a backend. Neo4J is a popular graph database. | ||
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See the `Neo4J how-to guide <https://linkml.io/linkml-store/how-to/Use-Neo4J.html>`_ for examples. | ||
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Does linkml-store support Solr? | ||
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | ||
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Currently we provide only read support for Solr. We are working on write support. | ||
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See the `Solr how-to guide <https://linkml.io/linkml-store/how-to/Query-Solr-using-CLI.html>`_ for examples. | ||
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Can I use linkml-store with my favorite triplestore? | ||
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | ||
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Not yet! This is a surprising omission given LinkML's roots in the semantic web community. However, | ||
this is planned soon, so check back later. | ||
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Data model | ||
---------- | ||
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What is the data model in linkml-store? | ||
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | ||
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linkml-store has a simple data model: | ||
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* A :class:`.Client` provides a top-level interface over one or more databases. | ||
* A :class:`.Database` consists of one or more possibly heterogeneous collections. | ||
* A :class:`.Collection` is a queryable set of objects of a similar type. | ||
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Search | ||
------ | ||
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Can I use LLM vector embeddings for search? | ||
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | ||
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Yes, you can use LLM vector embeddings for search. This is an optional feature. | ||
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See `How to use semantic search <https://linkml.io/linkml-store/how-to/Use-Semantic-Search.html>`_ for examples. | ||
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Do I need to use an LLM for search | ||
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | ||
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No, but currently other options are limited. You can use a naive tripartite index, or if your backend | ||
supports search out the box (e.g. Solr) then linkml-store should directly wire into this. | ||
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Validation | ||
---------- | ||
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Does linkml-store provide validation? | ||
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | ||
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Yes, linkml-store provides expressive validation using the LinkML framework. | ||
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Note that currently validation primarily leverages json-schema integrations, but the intent is to | ||
provide validation integrations directly with underlying backend stores. | ||
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Does linkml-store provide referential integrity validation? | ||
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | ||
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See `Check Referential Integrity <https://linkml.io/linkml-store/how-to/Check-Referential-Integrity.html>`_ for examples. | ||
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Inference | ||
--------- | ||
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What is inference in linkml-store? | ||
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | ||
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We have a very flexible notion of inference. It can encompass: | ||
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* Statistical or Machine Learning (ML) inference, e.g. via supervised learning | ||
* Ontological inference, e.g. via reasoning over an ontology | ||
* Rule-based or procedural inference | ||
* LLM-based inference | ||
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How do I do standard ML inference? | ||
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | ||
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Currently we provide integrations to scikit-learn, but only expose DecisionTree classifiers for now. | ||
Remember, linkml-store is not a full fledged ML platform; you should use packages like XGBoost, PyTorch, | ||
or scikit-learn directly for more complex ML tasks. | ||
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See `Predict Missing Data <https://linkml.io/linkml-store/how-to/Predict-Missing-Data.html>`_ for examples. | ||
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See also the `Command Line Tutorial <https://linkml.io/linkml-store/tutorials/Command-Line-Tutorial.html>`_ for | ||
a simple example. | ||
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How do I do LLM inference? | ||
~~~~~~~~~~~~~~~~~~~~~~~~~~~ | ||
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See the `Command Line Tutorial <https://linkml.io/linkml-store/tutorials/Command-Line-Tutorial.html>`_ (see | ||
the final section) for an example. | ||
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How do I do rule-based inference? | ||
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | ||
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Check back later for tutorials. For now, you can read about: | ||
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- the `LinkML expression language <https://linkml.io/linkml/schemas/expression-language.html>`_ | ||
- `Rules in LinkML <https://linkml.io/linkml/schemas/advanced.html#rules>`_ | ||
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In future we will provide bindings for rule engines, datalog engines, and OWL reasoners. |