Philipp Krenn

Make Your Data FABulous

Your Elasticsearch query returns the top 10 results. But what if the real top result is missing entirely? Here's why.

Make Your Data FABulous
#1about 7 minutes

Understanding the CAP theorem for distributed systems

The CAP theorem states that a distributed data store can only provide two of three guarantees: consistency, availability, and partition tolerance.

#2about 3 minutes

Introducing the FAB theory for datastore tradeoffs

The FAB theory proposes another set of tradeoffs for data stores, where you can only pick two of three attributes: fast, accurate, or big.

#3about 7 minutes

How terms aggregation trades accuracy for speed

Elasticsearch's terms aggregation may return inaccurate counts by default because each shard only considers its top local results to improve performance.

#4about 8 minutes

Inconsistent relevance scores in distributed full-text search

Full-text search relevance scores using TF-IDF can be inconsistent because inverse document frequency is calculated per-shard, not globally.

#5about 2 minutes

Using a single shard to ensure data accuracy

Forcing an index to use a single shard guarantees accurate aggregations and relevance scores by eliminating distributed calculations, but sacrifices horizontal scaling.

#6about 1 minute

Why you must consciously choose your data tradeoffs

It is crucial to understand and explicitly choose the tradeoffs in your data systems, like those in the CAP and FAB theorems, to avoid unexpected behavior.

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Matching moments

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02:56 MIN

Navigating the challenges of distributed aggregations

Distributed search under the hood

Q&A on indexing, aggregations, and OpenSearch vs Elasticsearch
03:31 MIN

Q&A on indexing, aggregations, and OpenSearch vs Elasticsearch

Search and aggregations made easy with OpenSearch and NodeJS

Optimizing compute, storage, and data transmission
05:32 MIN

Optimizing compute, storage, and data transmission

A Hitchhiker's Guide to Resource Efficient Software

Optimizing performance with advanced data distribution methods
04:58 MIN

Optimizing performance with advanced data distribution methods

Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases

Introducing the core principles of Elasticsearch
04:29 MIN

Introducing the core principles of Elasticsearch

Distributed search under the hood

Recapping Kafka's capabilities for real-time data feeds
01:17 MIN

Recapping Kafka's capabilities for real-time data feeds

Let's Get Started With Apache Kafka® for Python Developers

Distributing data using shards and replicas
02:40 MIN

Distributing data using shards and replicas

Distributed search under the hood

Achieving massive throughput with sharded architectures
05:47 MIN

Achieving massive throughput with sharded architectures

The Rise of Reactive Microservices

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