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    • A

      如何选择数据库
      • anneng

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    • A

      不同的数据岗位
      • anneng

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    • A

      cocalc
      • anneng

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    • A

      SQL执行顺序
      • anneng

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    • A

      apache data stack
      • anneng

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    • A

      生物信息领域github topic
      • anneng

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    • A

      spark在生信领域的应用
      • anneng

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    • A

      jupyter 架构
      • anneng

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      A

      https://jupyter-server.readthedocs.io/en/latest/
      5b5ca0b8-cad5-4413-8479-208fe053b179-image.png

      Jupyter Server contains the following components:

      ServerApp is the main Tornado-based application which connects all components together.

      Config Manager initializes configuration for the ServerApp. You can define custom classes for the Jupyter Server managers using this config and change SererApp settings. Follow the Config File Guide to learn about configuration settings and how to build custom config.

      Custom Extensions allow you to create the custom Server’s REST API endpoints. Follow the Extension Guide to know more about extending ServerApp with extra request handlers.

      Gateway Server is a web server that, when configured, provides access to Jupyter kernels running on other hosts. There are different ways to create a gateway server. If your ServerApp needs to communicate with remote kernels residing within resource-managed clusters, you can use Enterprise Gateway, otherwise, you can use Kernel Gateway, where kernels run locally to the gateway server.

      Contents Manager and File Contents Manager are responsible for serving Notebook on the file system. Session Manager uses Contents Manager to receive kernel path. Follow the Contents API guide to learn about Contents Manager.

      Session Manager processes users’ Sessions. When a user starts a new kernel, Session Manager starts a process to provision kernel for the user and generates a new Session ID. Each opened Notebook has a separate Session, but different Notebook kernels can use the same Session. That is useful if the user wants to share data across various opened Notebooks. Session Manager uses SQLite3 database to store the Session information. The database is stored in memory by default, but can be configured to save to disk.

      Mapping Kernel Manager is responsible for managing the lifecycles of the kernels running within the ServerApp. It starts a new kernel for a user’s Session and facilitates interrupt, restart, and shutdown operations against the kernel.

      Jupyter Client library is used by Jupyter Server to work with the Notebook kernels.

      Kernel Manager manages a single kernel for the Notebook. To know more about Kernel Manager, follow the Jupyter Client APIs documentation.

      Kernel Spec Manager parses files with JSON specification for a kernels, and provides a list of available kernel configurations. To learn about Kernel Spec Manager, check the Jupyter Client guide.

      0c508af6-fbf0-4f42-b0fb-a4468da9cdc2-image.png

      https://jupyter-server.readthedocs.io/en/latest/developers/rest-api.html

      https://jupyter-server.readthedocs.io/en/latest/operators/multiple-extensions.html
      One of the major benefits of Jupyter Server is that you can run serve multiple Jupyter frontend applications above the same Tornado web server. That’s because every Jupyter frontend application is now a server extension. When you run a Jupyter Server with multiple extensions enabled, each extension appends its own set of handlers and static assets to the server.

    • A

      sql执行顺序
      • anneng

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    • A

      jupyter 插件 2022
      • anneng

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    • A

      全文搜索jupyter notebook
      • anneng

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      A

      https://github.com/genostack/elasticsearch_loader
      Main features
      Batch upload CSV (actually any *SV) files to Elasticsearch
      Batch upload JSON files / JSON lines to Elasticsearch
      Batch upload parquet files to Elasticsearch
      Pre defining custom mappings
      Delete index before upload
      Index documents with _id from the document itself
      Load data directly from url
      SSL and basic auth
      Unicode Support v

    • A

      web 大文件的处理
      • anneng

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      A

      https://www.online-tech-tips.com/computer-tips/how-to-open-really-large-text-and-csv-files/

    • A

      superJupyter BI
      • anneng

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    • A

      jupyter conda
      • anneng

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    • A

      intermine和bluegene技术验证
      • anneng

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      Z

      docker run -p 5000:5000 --env-file /data_raid1/bioinfo/app/bluegene/bluegenes.env -v /data_raid1/bioinfo/app/bluegene/tools:/tools -d --restart unless-stopped intermine/bluegenes:latest

      docker run -d -v /data_raid1/bioinfo/app/jbrowse/jbrowse_conf.json:/conda/opt/jbrowse/jbrowse_conf.json -v /data_raid1/bioinfo/app/jbrowse/index.html:/conda/opt/jbrowse/index.html -p 8079:80 bokebiotech/jbrowser:v1.16.11

    • A

      Kubeflow MLflow
      • anneng

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      A

      76ce376f-97db-46b6-85d3-f5558fde5797-image.png
      https://medium.com/geekculture/enhancing-kubeflow-with-mlflow-8983373d0cac

    • A

      dagshub的生物学相关数据集
      • anneng

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      A

      https://developer.nvidia.com/blog/nvidia-rapids-accelerates-kubeflow-pipeline-with-gpus-on-kubernetes/
      Accelerating KubeFlow Pipeline with NVIDIA RAPIDS and GPUs on Kubernetes

    • A

      A powerful open source data warehouse system
      • anneng

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      A

      https://www.biostars.org/p/6857/
      Biomart Vs Intermine Vs Atlas

    • A

      数据仓库和数据湖的对比
      • anneng

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    • A

      Integrate Multiple Databases 多个数据库的集成
      • anneng

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