Delta Live Tables A to Z: Best Practices for Modern Data Pipelines

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  • เผยแพร่เมื่อ 24 ก.ค. 2023
  • Join Databricks' Distinguished Principal Engineer Michael Armbrust for a technical deep dive into how Delta Live Tables (DLT) reduces the complexity of data transformation and ETL. Learn what’s new; what’s coming; and how to easily master the ins-and-outs of DLT.
    Michael will describe and demonstrate:
    - What’s new in Delta Live Tables (DLT) - Enzyme, Enhanced Autoscaling, and more
    - How to easily create and maintain your DLT pipelines
    - How to monitor pipeline operations
    - How to optimize data for analytics and ML
    - Sneak Peek into the DLT roadmap
    Talk by: Michael Armbrust
    Connect with us: Website: databricks.com
    Twitter: / databricks
    LinkedIn: / databricks
    Instagram: / databricksinc
    Facebook: / databricksinc
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ความคิดเห็น • 27

  • @stevequan7306
    @stevequan7306 8 หลายเดือนก่อน +14

    This is the Bible for DLT! Worth to loop and study! Well done🙌

  • @jonathanduran2921
    @jonathanduran2921 7 หลายเดือนก่อน +15

    Ha, the CEO knowing where the raw data is stored.. almost died laughing there.

    • @hapslab
      @hapslab 5 หลายเดือนก่อน

      #databricks is an ecosystem now. Helped by all its amazing creators. Proud to be associated since 2015❤

  • @mrliuquantong4943
    @mrliuquantong4943 9 หลายเดือนก่อน +7

    Excellent Demo! Would you please provide the PDF file of this demo as well as the code for us to practise? looking forward to hearing from you.

  • @smedegaardpedersen
    @smedegaardpedersen 9 หลายเดือนก่อน +2

    Super good stuff.
    I wonder if the the function call inside the loop @1:13:22 should have been `create_report(r)` instead of `create_table(r)`?

  • @henryeleonu6237
    @henryeleonu6237 7 หลายเดือนก่อน

    interesting! I now have an idea of what delta live tables can do

  • @TheDataArchitect
    @TheDataArchitect 5 หลายเดือนก่อน

    43:10 this is awesome man.

  • @web3tel
    @web3tel 7 หลายเดือนก่อน

    I am not sure I understood the repeating references to the "errors in our docs"? Can you please clarify? What would be a reasone to publish docs with the errors, please? Is there quality control over these docs?

  • @mateen161
    @mateen161 6 หลายเดือนก่อน +1

    Would it be possible to create unmanaged tables with a location in datalake using DLT pipelines ?

  • @Rothbardo
    @Rothbardo 7 หลายเดือนก่อน

    anyone have a link to the slides?

  • @user-kx6ke9oy3v
    @user-kx6ke9oy3v 9 หลายเดือนก่อน +5

    where can i have the PPT? and demo code?

  • @user-kr1bf7vd3r
    @user-kr1bf7vd3r 6 หลายเดือนก่อน

    @michaelarmbrust2076 While using apply_changes, how do we handle duplicates in the sequence by column in a stateless way? Does dropDuplicates deduplicate data for the micro-batch like a forEachBatch would? or would it attempt to deduplicate the whole stream unless a watermark is given?

  • @user-kx6ke9oy3v
    @user-kx6ke9oy3v 7 หลายเดือนก่อน +1

    question here, why i run the same will get error "16:08:48 Running with dbt=1.6.2
    16:08:49 Registered adapter: databricks=1.6.4
    16:08:49 Unable to do partial parsing because saved manifest not found. Starting full parse.
    16:08:51 Found 2 models, 0 sources, 0 exposures, 0 metrics, 471 macros, 0 groups, 0 semantic models
    16:08:51
    16:14:02 Concurrency: 8 threads (target='databricks_cluster')
    16:14:02
    16:14:02 1 of 2 START sql streaming_table model default.device .......................... [RUN]
    16:14:03 1 of 2 OK created sql streaming_table model default.device ..................... [OK in 0.53s]
    16:14:03 2 of 2 START sql materialized_view model default.device_activity ............... [RUN]
    16:14:04 2 of 2 ERROR creating sql materialized_view model default.device_activity ...... [ERROR in 0.82s]
    16:14:04
    16:14:04 Finished running 1 streaming_table model, 1 materialized_view model in 0 hours 5 minutes and 12.60 seconds (312.60s).
    16:14:04
    16:14:04 Completed with 1 error and 0 warnings:
    16:14:04
    16:14:04 Runtime Error in model device_activity (models/example/device_activity.sql)
    [TABLE_OR_VIEW_NOT_FOUND] The table or view `main`.`default`.`device` cannot be found. Verify the spelling and correctness of the schema and catalog.
    If you did not qualify the name with a schema, verify the current_schema() output, or qualify the name with the correct schema and catalog."
    from my understanding the table only can created by DLT pipeline, DBT cannot create the table. but you succesd in create the streaming table and MV. May i know why?

  • @TheDataArchitect
    @TheDataArchitect 5 หลายเดือนก่อน

    37:10 no azure storage accounts?

  • @user-nv9fv2up5d
    @user-nv9fv2up5d หลายเดือนก่อน

    Quick Question : If a record is deleted from Source table hard delete how apply_changes cdc will handle ?

  • @irfana398
    @irfana398 8 หลายเดือนก่อน +2

    Why can't we run the code in the cell for debugging? I have found DLTs have so much limitation and hard to debug.

    • @alirezahassani3767
      @alirezahassani3767 8 หลายเดือนก่อน

      I had been eagerly anticipating the release of this feature for this year. Hopefully, they will add it soon.

    • @michaelarmbrust2076
      @michaelarmbrust2076 7 หลายเดือนก่อน

      We are working on a debugging experience that will be integrated with notebooks.

  • @saravananharisamy8085
    @saravananharisamy8085 5 หลายเดือนก่อน

    Please share the repo for cicd atleast

  • @oleksiy8105
    @oleksiy8105 4 หลายเดือนก่อน

    Straming=is always costly... If you trigger it manually or on schedule it is not streaming...

  • @spitfirexvii
    @spitfirexvii 6 หลายเดือนก่อน +1

    John Carmack, is that you?

  • @jhonsen9842
    @jhonsen9842 21 วันที่ผ่านมา

    This is the way how you can make Data engineer job easy and pay less to them.

  • @VerySeriousMan
    @VerySeriousMan 4 หลายเดือนก่อน

    Hard to follow unless you know a lot already.

  • @msftora3
    @msftora3 2 หลายเดือนก่อน

    just another stereotype reinvention of a wheel