PySpark SQL Recipes : with HiveQL, Dataframe and Graphframes / Raju Kumar Mishra and Sundar Rajan Raman
نوع المادة :
نصاللغة: الإنجليزية الناشر:[Berkeley, California] : Apress, 2019وصف:xxiv, 323 pages : illustrations ; 24 cmنوع المحتوى:- text
- computer
- online resource
- 9781484243343
- 1484243358
- 9781484243350
- QA76.73.P98 M574 2019
| نوع المادة | المكتبة الحالية | رقم الطلب | رقم النسخة | حالة | تاريخ الإستحقاق | الباركود | |
|---|---|---|---|---|---|---|---|
كتاب
|
UAE Federation Library | مكتبة اتحاد الإمارات General Collection | المجموعات العامة | QA76.73.P98 M574 2019 (إستعراض الرف(يفتح أدناه)) | C.1 | Library Use Only | داخل المكتبة فقط | 30030000000691 | ||
|
كتاب
|
UAE Federation Library | مكتبة اتحاد الإمارات General Collection | المجموعات العامة | QA76.73.P98 M574 2019 (إستعراض الرف(يفتح أدناه)) | C.2 | المتاح | 30030000000692 |
Introduction to PySpark SQL -- Installation -- 10 in PySpark SQL -- Operations on PySpark SQL DataFrames -- Data merging and data aggregation using PySparkSQL -- SQL, NoSQL, and PySparkSQL -- Optimizing PySpark SQL -- Structured streaming -- GraphFrames
Carry out data analysis with PySpark SQL, graphframes, and graph data processing using a problem-solution approach. This book provides solutions to problems related to dataframes, data manipulation summarization, and exploratory analysis. You will improve your skills in graph data analysis using graphframes and see how to optimize your PySpark SQL code. "PySpark SQL recipes" starts with recipes on creating dataframes from different types of data source, data aggregation and summarization, and exploratory data analysis using PySpark SQL. You'll also discover how to solve problems in graph analysis using graphframes. On completing this book, you'll have ready-made code for all your PySpark SQL tasks, including creating dataframes using data from different file formats as well as from SQL or NoSQL databases
