Apache Drill Book

Apache Drill Book
2024-01-23 09:52:59

Apache Drill Book

Introduction

An open-source software framework called Apache Drill allows data-intensive distributed applications for real-time examination of big datasets. primarily composed of contributions from MapR developers, Google's Dremel system, which is also sold as BigQuery, served as an inspiration for Drill. Drill is a top-level Apache project. The Apache Drill Project was started by Tom Shiran. In December 2016, the Apache Software Foundation named it a top-level project.

Alluxio, HBase, MongoDB, MapR-DB, HDFS, MapR-FS, Amazon S3, Azure Blob Storage, Google Cloud Storage, Swift, NAS, and local files are just a few of the NoSQL databases and file systems that Drill supports. Multiple datastores can be joined together in a single query. For instance, you might connect a directory of event logs in Hadoop with a user profile collection in MongoDB.

The query plan is automatically restructured by Drill's datastore-aware optimizer to take use of the datastore's built-in processing power. Additionally, if Drill and the datastore are on the same nodes, Drill supports data locality.

Recommended Books about Apache Drill in ML

An open-source SQL query engine called Apache Drill is made to swiftly and effectively analyze massive datasets kept in a variety of file formats, including JSON, CSV, Parquet, and more. Although Apache Drill was not created with machine learning in mind, it can be used as a component of a larger data processing pipeline that does.

The many capabilities and application cases of Apache Drill are covered in a number of books. However, you might want to think about books that cover more general subjects like data processing, big data, and machine learning pipelines if you are specifically interested in using Apache Drill for machine learning. Here are some suggestions:

  • Prashant Gupta's "Big Data Processing with Apache Spark": The different data processing activities covered in this book, including data cleaning, data wrangling, and data analysis, serve as an introduction to large data processing using Apache Spark. A chapter on using Apache Spark for machine learning is also included.
  • Aurélien Géron's "Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow": This book provides a thorough introduction to machine learning and covers a variety of subjects, including deep learning, neural networks, and supervised and unsupervised learning. Additionally, it offers exercises and real-world examples to aid in your machine learning process.
  • "Data Science for Business" by Tom Fawcett and Foster Provost: The subjects covered in this book's introduction to data science include data preparation, data analysis, and machine learning. It also has a chapter on big data, which explores the difficulties and possibilities of handling and analyzing enormous datasets.

These books may provide you a strong foundation in data processing and machine learning pipelines, which might be beneficial in combination with Apache Drill, even if they do not expressly concentrate on utilizing Apache Drill for machine learning.

Recommended books about Apache Drill

  • Rahul Kumar's "Learning Apache Drill": This book covers a wide range of subjects, including installation, setup, and data querying, and it offers a thorough introduction to Apache Drill. Additionally, it offers exercises and real-world examples to assist you in learning Apache Drill.
  • Paul Rogers' "Apache Drill in Action" This book covers subjects including data processing, query optimisation, and security and offers a more in-depth introduction to Apache Drill. Additionally, it provides case studies and real-world examples to help you comprehend how to apply Apache Drill in practical situations.
  • Jesse Anderson's "Apache Drill for SQL Analysts": This book covers subjects including querying nested data, merging several datasets, and enhancing query efficiency and offers a more focused introduction to Apache Drill for SQL analysts. Additionally, it offers exercises and real-world examples to help you master Apache Drill.
  • Sridhar Alla and Raghavendra Prabhu's "Big Data Analytics with Apache Spark and Apache Drill": This book covers a variety of data processing and analytics activities, such as data cleansing, data preparation, and machine learning, and introduces both Apache Spark and Apache Drill. In order to assist you comprehend how to utilise these tools to analyse and handle massive datasets, it also offers real-world examples and case studies.

These books may provide you a strong foundation in Apache Drill, from fundamental ideas to more complicated subjects. Additionally, they offer exercises and real-world examples to help you apply what you learn.