Making Apache Spark™ Better with Delta Lake

Join Michael Armbrust, head of Delta Lake engineering team, to learn about how his team built upon Apache Spark to bring ACID transactions and other data reliability technologies from the data warehouse world to cloud data lakes.
Apache Spark is the dominant processing framework for big data. Delta Lake adds reliability to Spark so your analytics and machine learning initiatives have ready access to quality, reliable data. This webinar covers the use of Delta Lake to enhance data reliability for Spark environments.
Topics areas include:
- The role of Apache Spark in big data processing
- Use of data lakes as an important part of the data architecture
- Data lake reliability challenges
- How Delta Lake helps provide reliable data for Spark processing
- Specific improvements improvements that Delta Lake adds
- The ease of adopting Delta Lake for powering your data lake
See full Getting Started with Delta Lake tutorial series here:
databricks.com...
Get the Delta Lake: Up & Running by O’Reilly ebook preview to learn the basics of Delta Lake, the open storage format at the heart of the lakehouse architecture. Download the ebook: dbricks.co/3II...

[@sonagy23]

28:32 How does Delta Lake work?
28:50 Delta On Disk
29:59 Table = result of a set of actions
31:31 Implementing Atomicity
32:48 Ensuring Serializability
33:33 Solving Conflicts Optimistically
35:08 Handling Massive Metadata
36:32 Roadmap
38:20 QnA

[@kbkonatham1701]

hi kim thanks for support , you are from ? , i am from india.

[@rakshithvenkatesh2773]

I see this whole "Hierarchical Data Pipeline" strategy being talked about quite a bit these days. We did establish this as part of a ready solution we built for Manufacturing use case using Confluent Kafka + KSQL. But the Data Lake is something i believe will remain/continue to exist as a depot for long term retention of data where AI/DA platforms leverage data from these data lakes for batch processing. I see this story from DataBricks to be a Data-warehouse convergence towards Data Lakes !

[@meryplays8952]

The architecture comes with a nice VLDB 2020 paper (which the presenter did not mention).

[@RossittoS]

Excellent features!!

[@hanssylvest8390]

Please give all empl. a better audio recording microphone.

[@jacekb4057]

Or use some AI audio cleaner :D

[@Sangeethsasidharanak]

27.28 on automating data quality. .. isn't it same as we do quality check before we save using custom code..Will there be any additional benefits?

[@gustavemuhoza4212]

It's probably the same, but not sure how you could do that on a datalake consistently. As described here, Delta appears to make it easier to do and making it possible to do it as if you were doing it on a relational database.

[@srh80]

Wait, people still use comcast and watch TV?

[@moebakry3203]

What is the best way to load data from Sql server to Delta lake every 5 seconds?

[@NicholasGabriel04]

debezium

[@hidemisuzuki965]

Where can I download the slides? Thanks!

[@rahulpathak3161]

Thank you and can you please share PPT..

[@user-ni4cp7lj6s]

www.slideshare.net/databricks/making-apache-spark-better-with-delta-lake

[@hanmuster]

@@user-ni4cp7lj6s Many thanks！