High performance Spark : best practices for scaling and optimizing Apache Spark

Data science & big data analytics : discovering, analyzing, visualizing and presenting data
Vydáno: (2015)

Scaling machine learning with Spark : distributed ML with MLlib, TensorFlow, and PyTorch
Autor: Polak, Adi
Vydáno: (2023)

Advanced analytics with PySpark : patterns for learning from data at scale using Python and Spark
Autor: Tandon, Akash
Vydáno: (2022)

Kafka : the definitive guide : real-time data and stream processing at scale
Autor: Narkhede, Neha
Vydáno: (2017)

Kafka : the definitive guide : real-time data and stream processing at scale
Autor: Shapira, Gwen
Vydáno: (2021)

The enterprise big data framework : building critical capabilities to win in the data economy
Autor: Middelburg, Jan-Willem
Vydáno: (2024)

Professional Hadoop
Autor: Antony, Benoy
Vydáno: (2016)

Introducing .NET for Apache Spark : distributed processing for massive datasets
Autor: Elliott, Ed
Vydáno: (2021)

Pro Apache Hadoop
Autor: Wadkar, Sameer
Vydáno: (2014)

Big data ztěžují zachování anonymity
Autor: Armerding, Taylor

Data mining and knowledge discovery for big data : methodologies, challenge and opportunities
Vydáno: (2014)

Introducing data science : big data, machine learning, and more, using Python tools
Autor: Cielen, Davy
Vydáno: (2016)

Azure databricks cookbook : accelerate and scale real-time analytics solutions using the apache spark-based analytics service
Autor: Raj, Phani
Vydáno: (2021)

Principles and practice of big data : preparing, sharing, and analyzing complex information
Autor: Berman, Jules J., 1950-
Vydáno: (2018)

Data algorithms with Spark : recipes and design patterns for scaling up using PySpark
Autor: Parsian, Mahmoud
Vydáno: (2022)

Data s přehledem : naučte se pracovat s daty a zajistěte si skvělou kariéru
Autor: Eremenko, Kirill
Vydáno: (2024)

Big data analytics beyond Hadoop : real-time applications with Storm, Spark and more Hadoop alternatives
Autor: Agneeswaran, Vijay Srinivas, 1977-
Vydáno: (2014)

Nechybujte při analýzách big dat
Autor: Violino, Bob

Jak vládnout velkým datům : aplikace big data governance v praxi
Autor: Stokláska, Ondřej

Nejběžnější projekty pro Hadoop a Spark
Autor: Oliver, Andrew C.

Applied data science using PySpark : learn the end-to-end predictive model-building cycle
Autor: Kakarla, Ramcharan
Vydáno: (2021)

Data science
Autor: Kelleher, John D., 1974-
Vydáno: (2018)

Big data : a tutorial-based approach
Autor: Raheem, Nasir
Vydáno: (2019)

Google BigQuery : the definitive guide : data warehousing, analytics, and machine learning at scale
Autor: Lakshmanan, Valliappa
Vydáno: (2019)

Numsense! data science for the layman : no math added
Autor: Ng, Annalyn
Vydáno: (2017)

Hybridní přístup k analytice
Autor: Dolejš, Radan

The internet of things and data analytics handbook
Vydáno: (2017)

Text data management and analysis : a practical introduction to information retrieval and text mining
Autor: Zhai, ChengXiang
Vydáno: (2016)

Mastering Tableau 2021 : implement advanced business intelligence techniques and analytics with Tableau
Autor: Meier, Marleen
Vydáno: (2021)

The data journalism handbook : towards a critical data practice
Vydáno: (2021)

Scaling big data with Hadoop and Solr : learn exciting new ways to build efficient, high performance enterprise search repositories for Big Data using Hadoop and Solr
Autor: Karambelkar, Hrishikesh, 1979-
Vydáno: (2013)

Využijte big data v reálném čase
Autor: Wu, Garrett

Data mesh : delivering data-driven value at scale
Autor: Dehghani, Zhamak
Vydáno: (2022)

Splunk certified study guide : prepare for the User, Power User, and Enterprise Admin certifications
Autor: Mehta, Deep
Vydáno: (2021)

Exploratory data mining and data cleaning
Autor: Dasu, Tamraparni
Vydáno: (2003)

Advances in knowledge discovery and data mining : 7th Pacific-Asia conference, PAKDD 2003 Seoul, Korea, April 30-May 2, 2003 : proceedings
Vydáno: (2003)