This year in Apache Lucene - 2019
As another year is coming to an end, let's take time to look at what happened in Lucene land in 2019.
As another year is coming to an end, let's take time to look at what happened in Lucene land in 2019.
With the addition of new data structures in Lucene 6.0, the Elasticsearch 5.0 release delivered massive indexing and search performance improvements for one-dimension numeric, date, and IP fields, and two-dimension (lat, lon) geo_point fields. Building on this work, the Elasticsearch 6.0 release further improved usability and simplicity of the geo_point API by setting the default indexing structure to the new block k-d tree (BKD) and removing all support for legacy prefix tree encoding.
As part of Elasticsearch 7.5.0, a new ingest processor — named enrich processor — was released. This new processor allows ingest node to enrich documents being ingested with additional data from reference data sets. This opens up a new world of possibilities for ingest nodes.
What does the revamped, modern technology stack of a 185-year-old Australian news corporation look like? In an industry that faces serious competition from anyone with a WordPress site and something to say, Nine Publishing, producer of Australia’s three largest news sites, sought to preserve a competitive edge by understanding how to enrich the experiences of their readers and journalists, while simultaneously identifying pain points and spotting problems before they happen.
This is a technical deep dive into the authentication process — a necessary first step before addressing the authorization decisions that are at the core of Elasticsearch security. The following will be a very detailed explanation of the inner workings of a key part of the authentication process: realms. If you'd prefer to start with a broader view of authentication (and authorization) in Elasticsearch, you may want to check out Demystifying authentication and authorization in Elasticsearch.
Elasticsearch is a powerful distributed search engine that has, over the years, grown into a more general-purpose NoSQL storage and analytics tool. The recent release of Elasticsearch 7 added many improvements to the way Elasticsearch works. It also formalized support for various applications including machine learning, security information and event management (SIEM), and maps, among others, through a revamped Kibana.
CHAOSSEARCH is building a new standard (a new category) in data analytics. Beyond the cost and complexity of Warehousing, Hadoop, or even Elasticsearch solutions. CHAOSSEARCH is a new kind of big data platform that delivers both search and analytics at a price and simplicity yet experienced. At CHAOS, we are primarily focused on transforming object storage (such as S3) into the first multi-model database, where the user provides read-only access to their S3 storage and CHAOS provides the rest.