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- Learning Spark: Lightning-Fast Data Analytics
Learning Spark: Lightning-Fast Data Analytics
85% of respondents would recommend this to a friend
€ 54
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What Stands Out
Detalji o proizvodu
- Explains the importance of structure and unification in Apache Spark for data processing
- Covers performing simple and complex data analytics and utilizing machine learning algorithms
- Provides guidance on learning Python, SQL, Scala, or Java high-level Structured APIs
- Demonstrates Spark operations, SQL Engine, and how to inspect, tune, and debug Spark operations
- Shows how to connect to various data sources such as JSON, Parquet, CSV, Avro, ORC, Hive, S3, or Kafka
- Includes information on performing analytics on batch and streaming data, building reliable data pipelines, and developing machine learning pipelines with open source Delta Lake and Spark
| Publisher | O'Reilly Media |
| Publication date | August 25, 2020 |
| Edition | 2nd |
| Language | English |
| Print length | 397 pages |
| ISBN-10 | 1492050040 |
| ISBN-13 | 978-1492050049 |
| Item Weight | 2.31 pounds (1.05 kg) |
| Dimensions | 7.25 x 1 x 9.25 inches (18.4 x 2.5 x 23.5 cm) |
Who Should Buy?
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Data Engineers
Ideal for data engineers seeking to enhance their skills in processing large datasets with Apache Spark.
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Data Scientists
Beneficial for data scientists wanting to speed up their data analytics processes and utilize big data efficiently.
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Beginner Learners
Great for those new to big data who seek a comprehensive introduction to Spark and its capabilities.
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Casual Users
Not suitable for casual users who need basic data skills without the complexity of big data frameworks.
OPIS PROIZVODA
Learning Spark: Lightning-Fast Data Analytics
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Software Development Editorial Review
The second edition of "Learning Spark: Lightning-Fast Data Analytics" is praised for its detailed coverage of concepts related to Spark architecture, parallelization, and optimizing analytical pipelines. Reviewers appreciate the comprehensive section on delta lake and the detailed explanation of MLflow and ML algorithms in parallel. It is described as a valuable supplementary resource for studying Databricks certifications. However, some reviewers note that the book may be too basic for those already familiar with Spark.
Customer Reviews & Ratings
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5 zvjezdica
100%
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4 zvjezdica
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3 zvjezdica
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2 zvjezdica
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1 zvjezdica
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Pros
- Comprehensive coverage of Spark architecture and analytical pipeline optimization
- Detailed section on delta lake and MLflow
- Valuable supplementary resource for Databricks certifications
- Clear instructions for setting up Spark shell and installing Spark locally
- Useful information on the inner workings of Spark and its UI
Protiv
- May be too basic for those with prior experience using Spark
Product Price History
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