abhishek-kathuria / Big-Data-Spark-Inverted-Index

This project is about implementing an inverted index using Apache Spark (PySpark) for building the index and a relational database (e.g. SQLite) for storing the index.

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Big-Data-Spark-Inverted-Index 🤘

This project is about implementing an inverted index using Apache Spark for building the index and a relational database (e.g. SQLite) for storing the index. We are using Python (PySpark) for this project. Storing the index in a database offers the benefit of using the B-Tree data structure offered by a relational database instead of building it from the scratch.

Implementation ☁️

  1. Build the index using a document collection.
  2. Create database tables for storing the inverted index.
  3. Implement the keyword search functionality.
  4. Implement result ranking using the TF-IDF measure and cosine similarity
  5. Implement a simple interface for giving keyword queries and showing results.

Packages and Software used 💻

Python(Pyspark)
SQLite
NLTK package
Google Colab

Insights 📝

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About

This project is about implementing an inverted index using Apache Spark (PySpark) for building the index and a relational database (e.g. SQLite) for storing the index.


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