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BITS Pilani Hyderabad | 003-007 | General Stack (For lending) | 005.133 MIS-R (Browse shelf(Opens below)) | Available | 45596 |
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| 005.133 MET-S Design patterns in Java / | 005.133 MIL-C Python projects for begineers : a ten-week bootcamp approach to python programming / | 005.133 MIl-R Begin to code with python / | 005.133 MIS-R Ryspark SQL recipes : with HiveQL, dataframe and graphframes / | 005.133 MIS-R PySpark recipes : a problem-solution approach with PySpark2 / | 005.133 MIT-M C programming / | 005.133 MOH-K Data science with raspeherry Pi : real-time applications using a localized cloud / |
Carry out data analysis using a problem-solution approach with PySpark SQL, graph frames, and graph data processing. This book provides solutions to problems related to data frames, data manipulation summarization, and exploratory analysis. You will improve your skills in graph data analysis using graph frames and see how to optimize your PySpark SQL code. "PySpark SQL recipes" start with recipes for creating data frames from different types of data sources, data aggregation and summarization, and exploratory data analysis using PySpark SQL. You'll also discover how to solve problems in graph analysis using graph frames. On completing this book, you'll have ready-made code for all your PySpark SQL tasks, including creating data frames using data from different file formats aandSQL or NoSQL databases.
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