Data Algorithms with Spark: Recipes and Design Patterns for...

Main
Computers - Algorithms and Data Structures
Data Algorithms with Spark: Recipes and...

Data Algorithms with Spark: Recipes and Design Patterns for Scaling Up using PySpark

Mahmoud Parsian

5.0 / 5.0

ఈ పుస్తకం ఎంతగా నచ్చింది?

దింపుకొన్న ఫైల్ నాణ్యత ఏమిటి?

పుస్తక నాణ్యత అంచనా వేయడాలనుకుంటే దీన్ని దింపుకోండి

దింపుకొన్న ఫైళ్ళ నాణ్యత ఏమిటి?

వర్గాలు:

Computers - Algorithms and Data Structures

సంవత్సరం:

2022

ముద్రణం:

1

ప్రచురణకర్త:

O'Reilly Media

భాష:

english

పేజీల సంఖ్య:

438

ISBN 10:

1492082384

ISBN 13:

9781492082385

ఫైల్:

PDF, 12.58 MB

IPFS:

,

english, 2022

ఆన్‌లైన్‌లో చదవండి

దింపుకోలు (pdf, 12.58 MB)

కి మార్పిడి జరుగుతూ ఉంది.

కి మార్పిడి విఫలమైంది!

మీకు ఆసక్తిగా కనిపించ వచ్చు

Mark Needham — Building Real-Time Analytics Systems: From Events to Insights with Apache Kafka and Apache Pinot

Guy Harrison, Jesse Seldess, Ben Darnell — CockroachDB The Definitive Guide: Distributed Data at Scale

Carl Allchin — Communicating with Data: Making Your Case With Data

Thomas Nield — Essential Math for Data Science

Akash Tandon & Sandy Ryza & Uri Laserson & Sean Owen & Josh Wills — Advanced Analytics with PySpark

Akash Tandon, Sandy Ryza, Uri Laserson, Sean Owen, Josh Wills — Advanced Analytics with Pyspark

Denny Lee, Tathagata Das, and Vini Jaiswal — Delta Lake: The Definitive Guide

Adi Polak — Scaling Machine Learning with Spark: Distributed ML with MLlib, TensorFlow, and PyTorch

Chip Huyen — Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications

Chip Huyen — Designing Machine Learning Systems

Joe Reis, Matt Housley — Fundamentals of Data Engineering

Barr Moses, Lior Gavish, Molly Vorwerck — Data Quality Fundamentals: A Practitioner's Guide to Building Trustworthy Data Pipelines

Christian Ciceri, Dave Farley, Neal Ford, Andrew Harmel-Law, Michael Keeling, Carola Lilienthal, João Rosa, Alexander von Zitzewitz, René Weiss, Eóin Woods — Software Architecture Metrics: Case Studies to Improve the Quality of Your Architecture

Justin Domingus, John Arundel — Cloud Native Devops with Kubernetes: Building, Deploying, and Scaling Modern Applications in the Cloud, 2nd Edition

Holden Karau, Boris Lublinsky — Scaling Python with Ray: Adventures in Cloud and Serverless Patterns

Valliappa Lakshmanan — Data Science on the Google Cloud Platform: Implementing End-to-End Real-Time Data Pipelines: From Ingest to Machine Learning

Holden Karau, Mika Kimmins — Scaling Python with Dask: From Data Science to Machine Learning

Brian Buzzelli — Data Quality Engineering in Financial Services: Applying Manufacturing Techniques to Data

Rui Pedro Machado, Helder Russa — Analytics Engineering with SQL and dbt: Building Meaningful Data Models at Scale

Daniel Vaughan — Data Science: The Hard Parts: Techniques for Excelling at Data Science

Michael Shearer — Hands-On Entity Resolution: A Practical Guide to Data Matching With Python

James Serra — Deciphering Data Architectures: Choosing Between a Modern Data Warehous, Data Fabric, Data Lakehouse, and Data Mesh

James Serra — Deciphering Data Architectures: Choosing Between a Modern Data Warehouse, Data Fabric, Data Lakehouse, and Data Mesh

Joe Minichino — Data Analytics in the AWS Cloud: Building a Data Platform for BI and Predictive Analytics on AWS

Donald Miner, Adam Shook — MapReduce Design Patterns: Building Effective Algorithms and Analytics for Hadoop and Other Systems

Mahmoud Parsian — Data Algorithms: Recipes for Scaling Up with Hadoop and Spark

Bill (B.) Chambers, Matei (M.) Zaharia — Spark: The Definitive Guide: Big Data Processing Made Simple

Gerard Maas, Francois Garillot — Stream Processing with Apache Spark: Mastering Structured Streaming and Spark Streaming

Shannon Bradshaw; Eoin Brazil; Kristina Chodorow — MongoDB: The Definitive Guide: Powerful and Scalable Data Storage 3rd Edition

Sandy Ryza, Uri Laserson, Sean Owen, Josh Wills — Advanced Analytics with Spark: Patterns for Learning from Data at Scale, Second Edition

Fabian Hueske, Vasiliki Kalavri — Stream Processing with Apache Flink: Fundamentals, Implementation, and Operation of Streaming Applications

Gwen Shapira, Todd Palino, Rajini Sivaram, Krit Petty — Kafka: The Definitive Guide: Real-Time Data and Stream Processing at Scale

Jules S. Damji, Brooke Wenig, Tathagata Das, Denny Lee — Learning Spark: Lightning-Fast Data Analytics

Harry Percival, Bob Gregory — Architecture Patterns with Python

Luk Arbuckle, Khaled El Emam — Building an Anonymization Pipeline: Creating Safe Data

Piethein Strengholt — Data Management at Scale: Best Practices for Enterprise Architecture

Tobias Macey — 97 Things Every Data Engineer Should Know

Chris Fregly, Antje Barth — Data Science on AWS: Implementing End-to-End, Continuous AI and Machine Learning Pipelines

Nikhil Buduma — Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms, 2nd Edition

Mahmoud Parsian — Data Algorithms with Spark: Recipes and Design Patterns for Scaling Up using PySpark (Early Release)

Mahmoud Parsian — Data Algorithms with Spark (Sixth Early Release)

Mahmoud Parsian — Data Algorithms with Spark

కీలక పదబంధాలు

సంబంచిన పుస్తక జాబితాలు