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  • JetBrains Tools for Data Science & Big Data

    https://www.jetbrains.com/data-tools/

    PyCharm for Data Science

    PyCharm Professional Edition integrates with Jupyter Notebook to combine the interactive nature of Jupyter Notebook with the benefits of the most intelligent Python IDE. In addition to the built-in Python coding assistance, you can also install a plugin that adds the R support.

    Intelligent Jupyter notebooks

    PyCharm combines the full intelligence of its code editor with the collaborative and interactive capabilities of Jupyter notebooks. Work with local or remote Jupyter notebooks as you would do in a web-based Jupyter application, but with intelligent coding assistance and overall ergonomics the IDE provides to let you keep your focus on the code and the data.

    Conda integration

    PyCharm makes it easy for you to create and select the right environment — keep your dependencies isolated by having separate Conda environments per project.

    Jupyter Notebook debugger

    Jupyter Notebook integration not only includes auto-completion, navigation and code analysis, but provides a full-featured graphical debugger with the ability to step into declarations.

    Scientific libraries and plots

    PyCharm has built-in support for scientific libraries. It supports Pandas, Numpy, Matplotlib, and other scientific libraries, offering you best-in-class code intelligence, graphs, array viewers and much more.

    Try PyCharm and make it a new home for your data science experiments

     

    IntelliJ IDEA for Data Engineers

    Big Data Tools is a plugin for IntelliJ IDEA Ultimate that is tailored to the needs of data engineers, data scientists, data analysts, and ML engineers.

    Intelligent Zeppelin notebooks

    Enjoy IntelliJ IDEA’s famous coding assistance for working with Zeppelin notebooks. The plugin offers smart navigation, code completion, inspections & quick-fixes, and refactorings inside the notebooks.

    Integrated Spark and Hadoop tools

    Manage and monitor your Spark and Hadoop applications, inspect your Spark jobs execution in an IDE tool window – just as you would do it using Spark History Server or Hadoop Web UI.

    Distributed file systems and columnar formats

    The plugin allows you to connect to remote file systems, such as HDFS, or S3, and conveniently work with the files. Browse buckets and folders, search for files, move, create, rename folders and files without leaving the IDE. The plugin supports Parquet and other columnar file formats.

    Tools for table data and charts

    While notebooks offer the original intelligent experience of the IDE editor, they seamlessly integrate a rich set of tools for working with paragraphs’ output, table data, and charts. You get the full functionality of Zeppelin notebooks embedded into the notebook editor. Browse table data, switch between various chart types, export data, and a lot more – without breaking your flow.

    Install Big Data Tools to make IntelliJ IDEA Ultimate you get-go tool to run Spark jobs, manage Spark and Hadoop application, and to work with the data across distributed storages

     

    DataGrip for Data Warehouses

    SQL remains one of the most convenient and efficient ways to work with large data, be it a relational database or a data warehouse. Regardless of the type of data, as long as it offers the SQL interface, DataGrip offers the most ergonomic environment to run SQL queries and browse table data.

    Intelligent SQL query console

    Allows you to execute queries in different modes and provides a local history that keeps track of all your activity and protects you from losing your work.

    Database schema navigation

    Lets you jump to any table, view, or procedure by its name via the corresponding action, or directly from its usages in the SQL code.

    Add DataGrip to your toolset in order to master your SQL queries and run them efficiently and conveniently.

     

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  • 原文地址:https://www.cnblogs.com/dhcn/p/13365692.html
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