Notebooks in Azure Databricks

Brad Llewellyn takes us through Azure Databricks notebooks:

Azure Databricks Notebooks support four programming languages, Python, Scala, SQL and R.  However, selecting a language in this drop-down doesn’t limit us to only using that language.  Instead, it makes the default language of the notebook.  Every code block in the notebook is run independently and we can manually specify the language for each code block.

Before we get to the actually coding, we need to attach our new notebook to an existing cluster.  As we said, Notebooks are nothing more than an interface for interactive code.  The processing is all done on the underlying cluster.

Read on to learn how Databricks uses the notebook metaphor heavily in how you interact with it.

Related Posts

Comparing Performance: HBase1 vs HBase2

Surbhi Kochhar takes us through performance improvements between HBase version 1 and HBase version 2: We are loading the YCSB dataset with 1000,000,000 records with each record 1KB in size, creating total 1TB of data. After loading, we wait for all compaction operations to finish before starting workload test. Each workload tested was run 3 […]

Read More

The Transaction Log in Delta Tables

Burak Yavuz, et al, explain how the transaction log works with Delta Tables in Apache Spark: When a user creates a Delta Lake table, that table’s transaction log is automatically created in the _delta_log subdirectory. As he or she makes changes to that table, those changes are recorded as ordered, atomic commits in the transaction log. Each commit […]

Read More

Categories

July 2019
MTWTFSS
« Jun Aug »
1234567
891011121314
15161718192021
22232425262728
293031