Although I work in a variety of IDEs, my go-to choices are JetBrains P圜harm for Python (including for PySpark and Jupyter Notebook development) and JetBrains IntelliJ for Java and Scala (including Apache Spark development). Within the domains of data science, big data analytics, and data analysis, languages such as SQL, Python, Java, Scala, and R are common. According to the PYPL Index, the ten most popular, current IDEs are: The choice of IDE may depend on one’s predominant programming language. Full-Featured IDEĪlthough the Athena Query Editor is fairly functional, many Engineers perform a majority of their software development work in a fuller-featured IDE. Access to AWS Glue data sources is also available from within the Editor. The Editor can convert SELECT queries to CREATE TABLE AS ( CTAS) and CREATE VIEW AS statements. Queries can be run directly from the Editor, saved for future reference, and query results downloaded. The Athena Query Editor has many of the basic features Data Engineers and Analysts expect, including SQL syntax highlighting, code auto-completion, and query formatting. In the previous post, Getting Started with Data Analysis on AWS using AWS Glue, Amazon Athena, and QuickSight, we used the Athena Query Editor to construct and test SQL queries against semi-structured data in an S3-based Data Lake. In addition to Presto, Athena also uses Apache Hive to define tables. Athena is ideal for quick, ad-hoc querying, but it can also handle complex analysis, including large joins, window functions, and arrays. According to AWS, the Athena query engine is based on Presto 0.172. The underlying technology behind Amazon Athena is Presto, the popular, open-source distributed SQL query engine for big data, created by Facebook. Amazon Athena supports and works with a variety of popular data file formats, including CSV, JSON, Apache ORC, Apache Avro, and Apache Parquet. Executing Amazon Athena Queries from JetBrains P圜harmĪccording to Amazon, Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL.
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