Blog for Vespa - The open big data serving engine
How I learned Vespa by thinking in Solr
Learning Vespa in terms of Solr analogies can help flatten the learning curve.
24 Feb 2021
Parent-child joins and tensors for content recommendation
A real-world application of parent-child joins and tensor functions to model topic popularity for content recommendation.
22 Feb 2021
How Using Screwdriver for CI/CD Reduced Vespa’s Time Spent on Builds and Pull Requests by 75%
Introducing Screwdriver for Vespa's CI/CD needs.
22 Feb 2021
Build a basic text search application from python with Vespa
Introducing pyvespa simplified API. Build Vespa application from python with few lines of code.
18 Feb 2021
Using approximate nearest neighbor search to find similar products
Approximate nearest neighbor search demonstration using Amazon Product dataset
Jo Kristian Bergum
16 Feb 2021
Q&A from “The Great Search Engine Debate - Elasticsearch, Solr or Vespa?” Meetup
This blog post addresses the Vespa-related questions, with quicklinks into the recording for easy access. We have also responded to the unanswered questions from the chat log.
08 Feb 2021
Vespa Product Updates, January 2021
Advances in Vespa features and performance last month include Automatic Reindexing, Tensor Optimizations and Explainlevel Query Parameter for easier query blueprint tracing.
02 Feb 2021
Using approximate nearest neighbor search in real world applications
From text search and recommendation to ads and online dating, ANN search rarely works in isolation.
18 Dec 2020
Vespa Product Updates, December 2020
Advances in Vespa features and performance include improved tensor ranking performance, Apache ZooKeeper integration, Vespa Python API for researchers and ONNX integration.
17 Dec 2020
Stateful model serving: how we accelerate inference using ONNX Runtime
There's a difference between stateless and stateful model serving.
14 Dec 2020
Fine-tuning a BERT model for search applications
How to ensure training and serving encoding compatibility.
25 Nov 2020
From research to production: scaling a state-of-the-art machine learning system
How we implemented a production-ready question-answering application and reduced response time by more than two orders of magnitude.
12 Nov 2020
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