explaingit

ngaut/deepbloom-1

Analysis updated 2026-07-18 · repo last pushed 2018-12-15

JavaAudience · developerComplexity · 4/5DormantSetup · hard

TLDR

DeepBloom uses a trained machine learning model instead of a traditional Bloom filter to quickly and efficiently check whether an item exists in a dataset.

Mindmap

mindmap
  root((deepbloom-1))
    What it does
      Learned Bloom filter
      Predicts set membership
      Sandwiched variant included
    Tech stack
      Java
      Apache Spark
      Machine learning models
    Use cases
      Fast database lookups
      Cache membership checks
      Large-scale data pipelines
    Audience
      Backend engineers
      Systems researchers

Code map

Detail Auto

An interactive map of this repo's files and how they connect — its source is parsed live in your browser. Click Visualize to build it.

filefunction / class

What do people build with it?

USE CASE 1

Check whether a user ID likely exists before running a more expensive database lookup

USE CASE 2

Have a cache quickly decide if an item is worth retrieving without a full query

USE CASE 3

Experiment with learned data structures as a faster alternative to hash-based Bloom filters

USE CASE 4

Process large training datasets with Apache Spark to build a membership-prediction model

What is it built with?

JavaApache Spark

How does it compare?

ngaut/deepbloom-1abhishek-kumar09/pmdahus1/cdt
LanguageJavaJavaJava
Last pushed2018-12-152020-11-152024-11-05
MaintenanceDormantDormantStale
Setup difficultyhardmoderatemoderate
Complexity4/53/53/5
Audiencedeveloperdeveloperdeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · hard Time to first run · 1day+

Requires Apache Spark and upfront model training time before it delivers speed benefits.

Copy-paste prompts

Prompt 1
Explain how a learned Bloom filter differs from a traditional hash-based Bloom filter.
Prompt 2
Show me how to train DeepBloom's basic learned Bloom filter on a sample dataset.
Prompt 3
What does the sandwiched Bloom filter approach do differently, and when should I use it?
Prompt 4
Help me set up Apache Spark to run DeepBloom's training pipeline on a larger dataset.
Prompt 5
Walk me through the performance test files to see how DeepBloom compares to a standard Bloom filter.

Frequently asked questions

What is deepbloom-1?

DeepBloom uses a trained machine learning model instead of a traditional Bloom filter to quickly and efficiently check whether an item exists in a dataset.

What language is deepbloom-1 written in?

Mainly Java. The stack also includes Java, Apache Spark.

Is deepbloom-1 actively maintained?

Dormant — no commits in 2+ years (last push 2018-12-15).

How hard is deepbloom-1 to set up?

Setup difficulty is rated hard, with roughly 1day+ to a first successful run.

Who is deepbloom-1 for?

Mainly developer.

Open on GitHub → Explain another repo

This repo across BitVibe Labs

Verify against the repo before relying on details.

Alternatives & similar repos