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WeAreDevelopers LIVE • Jun 1, 2023

Using WebAssembly for in-database Machine Learning

Akmal Chaudhri

Tired of building expensive ETL pipelines just to run machine learning models? Learn how WebAssembly lets you execute secure, near-native ML workloads directly inside your database.

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#1 about 3 min

Introduction to WebAssembly for in-database machine learning

An overview of utilizing WebAssembly to execute machine learning modules directly within a database management system.

#2 about 2 min

Evolution of distributed SQL database management systems

How modern distributed relational databases enable horizontal scaling for analytical and operational workloads.

#3 about 3 min

Options for database machine learning integration architectures

Utilizing tools like Apache Spark, Python libraries, and vector embeddings to perform machine learning near or within databases.

#4 about 4 min

Benefits of executing WebAssembly natively in databases

How WebAssembly addresses complex procedural SQL, provides data co-location, and reduces developer effort for data science tasks.

#5 about 4 min

Architectural flow of WebAssembly inside a DBMS

The process of compiling business logic in languages like Rust or C++ and executing it within a secure database sandbox.

#6 about 3 min

Setting up the Wasm SDK and Rust toolchain

Instructions for downloading and configuring the WebAssembly SDK and Bytecode Alliance tools for local development.

#7 about 2 min

Preparing local tools to push Wasm executable modules

Cloning and building the push-wasm GitHub dependency tool to bridge compiled modules into SingleStore.

#8 about 3 min

Defining Wit interfaces and declaring Rust backend dependencies

Configuring an interface definition file to specify input and output types for a VADER sentiment algorithm.

#9 about 4 min

Compiling and uploading Rust logic into the DBMS

Creating the actual sentiment scoring function in Rust and pushing it to the database for use as a user-defined function.

#10 about 3 min

Testing sentiment inference behavior via SQL select statements

Verifying the WebAssembly function behavior on text patterns like capitalization and exclamation points directly inside standard SQL queries.

#11 about 6 min

Live demo applying sentiment analysis on an IMDB dataset

Applying the deployed Rust WebAssembly module across an IMDB review table to batch-compute machine learning scores without ETL.

#12 about 4 min

Key takeaways and developer resources for WebAssembly integration

A summary of WebAssembly extensibility capabilities along with resources from the Bytecode Alliance.

#13 about 23 min

Audience Q&A on language support, performance, and tradeoffs

A community discussion focusing on dynamic language support, native performance comparisons, testing workflows, and potential cloud provider implementations.

Matching moments

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