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Data Engineering
Join discussions on data engineering best practices, architectures, and optimization strategies within the Databricks Community. Exchange insights and solutions with fellow data engineers.
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Forum Posts

User16789201666
by Databricks Employee
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Resolved! With SQL ACL’s, who can DROP a table?

Can the database owner always drop a table?

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Latest Reply
User16789201666
Databricks Employee
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Table owner or administrator. Before DBR 7.x, the database owner can. As of DBR 7.x, the database owner cannot. This will be changing soon.

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Anonymous
by Not applicable
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What's the best way to develop Apache Spark Jobs from an IDE (such as IntelliJ/Pycharm)?

A number of people like developing locally using an IDE and then deploying. What are the recommended ways to do that with Databricks jobs?

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Anonymous
Not applicable
  • 1 kudos

The Databricks Runtime and Apache Spark use the same base API. One can create Spark jobs that run locally and have them run on Databricks with all available Databricks features.It is required that one uses SparkSession.builder.getOrCreate() to create...

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User16783854357
by New Contributor III
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How to run a Delta Live Table pipeline with a different runtime?

I would like to run a DLT pipeline with the 8.2 runtime.

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User16783854357
New Contributor III
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You can add the below JSON property to the Delta Live Table pipeline specification at the parent level:"dbr_version": "8.2"

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User16776430979
by New Contributor III
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How to optimize and convert a Spark DataFrame to Arrow?

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...

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Anonymous
by Not applicable
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Resolved! Configuring airflow

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?

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User16783855117
Contributor II
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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...

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Anonymous
by Not applicable
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Anonymous
Not applicable
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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

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Anonymous
by Not applicable
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User16783855117
Contributor II
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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...

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Anonymous
by Not applicable
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Resolved! Best practices to query logs

We dump our logs in S3 currently. Can you give us best practices to make these logs easier to query?

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sajith_appukutt
Honored Contributor II
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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

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Anonymous
by Not applicable
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Resolved! Backfill Delta table

What is the recommended way to backfill a delta table using a series of smaller date partitioned jobs?

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User16783855117
Contributor II
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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...

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User16776430979
by New Contributor III
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How to optimize conversion between PySpark and Arrow?

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 ...

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User16790091296
by Contributor II
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Some Tips & Tricks for Optimizing costs and performance (Clusters and Ganglia): [Note: This list is not exhaustive] Leverage the DataFrame or Spar...

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...

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Anonymous
by Not applicable
  • 3071 Views
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Resolved! Delta vs parquet

When does it make sense to use Delta over parquet? Are there any instances when you would rather use parquet?

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Latest Reply
Ryan_Chynoweth
Esteemed Contributor
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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...

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