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GitHub / RJBarker / home_sales
Use PySpark and SparkSQL to execute SQL queries through a temporary view of the DataFrame created. Conduct additional queries on cached and partitioned data to determine runtime comparisons.
JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RJBarker%2Fhome_sales
Stars: 0
Forks: 0
Open Issues: 0
License: None
Language: Jupyter Notebook
Repo Size: 146 KB
Dependencies:
0
Created: 4 months ago
Updated: 4 months ago
Last pushed: 4 months ago
Last synced: 4 months ago
Topics: big-data, big-data-analytics, cached, large-scale, partitioning, pyspark, pyspark-dataframes, python, sparksql
Files
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