Example use case: When connecting a sample Plotly Dash application to a large dataset, in order to test the performance, I need the file format to be in either hdf5 or arrow. According to this doc: Optimize conversion between PySpark and pandas DataF...
Should we create a Databricks user for airflow and generate a personal access token for it? We also have gsuite SSO enabled, does that mean I need to create a gsuite account for the user as well?
I would recommend having the 'user' the Databricks Jobs are triggered by as a dedicated user. This is what I would consider a 'Service Account' and I'll drop a definition for that type of user below.Seeing that you have SSO enabled, I might create th...
Full support for Databricks Runtime versions lasts for six months, with the exception of Long Term Support (LTS) versions, which Databricks supports for two years.https://docs.databricks.com/release-notes/runtime/databricks-runtime-ver.html
It really depends on your business intentions! You can remove files no longer referenced by a Delta table and are older than the retention threshold by running the vacuum command on the table. vacuum is not triggered automatically. The default retent...
We dump our logs in S3 currently. Can you give us best practices to make these logs easier to query?
And if it is generic logs which gets landed on S3 , it'd be worth taking a look at Autoloader. Here is a blog post on processing crowdstrike logs in a similar way
What is the recommended way to backfill a delta table using a series of smaller date partitioned jobs?
Another approach you might consider is creating a template notebook to query a known date range with widgets. For example, two date widgets, start time and end time. Then from there you could use Databricks Jobs to update these parameters for each ru...
Seems like you can convert between dataframes and Arrow objects by using Pandas as an intermediary, but there are some limitations (e.g. it collects all records in the DataFrame to the driver and should be done on a small subset of the data, you hit ...
After I enable one of my Delta tables to use Change Data Feed, does it record all previous changes to my table?
Some Tips & Tricks for Optimizing costs and performance (Clusters and Ganglia):[Note: This list is not exhaustive]Leverage the DataFrame or SparkSQL API’s first. They use the same execution process resulting in parity in performance but they also com...
When does it make sense to use Delta over parquet? Are there any instances when you would rather use parquet?
Users should almost always choose Delta over parquet. Keep in mind that delta is a storage format that sits on top of parquet so the performance of writing to both formats is similar. However, reading data and transforming data with delta is almost a...
An Action in Spark is any operation that does not return an RDD. Evaluation is executed when an action is taken. Actions trigger the scheduler, which build a directed acyclic graph (DAG) as a plan of execution. The plan of execution is created by wor...
When and why should I convert b/w a Pandas to Koalas dataframe? What are the implications?
Koalas is distributed on a Databricks cluster similar to how Spark dataframes are also distributed. Pandas dataframes only live on the spark driver in memory. If you are a pandas user and are using a multi-node cluster then you should use koalas to p...
I’m using the databricks-snowflake connector to load data into a Snowflake table. Can someone point me to any example of how we can append only a subset of columns to a target Snowflake table (for example some columns in the target snowflake table ar...
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