deco | Python-like decorator in Rust | Reactive Programming library

I would add the following option if you want to use jks

Please have a look at the official deployment guideline here: https://spark.apache.org/docs/latest/structured-streaming-kafka-integration.html#deploying

Extracting the important part:

Instead of using a button, I used input of type checkbox to style the dropdown when its open and remove the style when its closed. button won't work because they require either JavaScript to add functions or be inside a form element (to act as a submit button which is not what you want here).

The error message you got:

py4j.Py4JException: Method and([class java.lang.Boolean]) does not exist

This means you're trying to apply AND operator between a Column expression and a literal Boolean value.

You need change this part:

You can't use connector compiled for Scala 2.11 with Spark 3.2.0 that is compiled with Scala 2.12. You need to use appropriate version - right now it's 3.1.0 with coordinates com.datastax.spark:spark-cassandra-connector_2.12:3.1.0

P.S. Please note that although basic functionality will work, more advanced functionality won't work until the SPARKC-670 is fixed (see this PR)

ABFS is a "real" file system, so the S3A zero rename committers are not needed. Indeed, they won't work. And the client is entirely open source - look into the hadoop-azure module.

the ADLS gen2 store does have scale problems, but unless you are trying to commit 10,000 files, or clean up massively deep directory trees -you won't hit these. If you do get error messages about Elliott to rename individual files and you are doing Jobs of that scale (a) talk to Microsoft about increasing your allocated capacity and (b) pick this up https://github.com/apache/hadoop/pull/2971

This isn't it. I would guess that actually you have multiple jobs writing to the same output path, and one is cleaning up while the other is setting up. In particular -they both seem to have a job ID of "0". Because of the same job ID is being used, what only as task set up and task cleanup getting mixed up, it is possible that when an job one commits it includes the output from job 2 from all task attempts which have successfully been committed.

I believe that this has been a known problem with spark standalone deployments, though I can't find a relevant JIRA. SPARK-24552 is close, but should have been fixed in your version. SPARK-33402 Jobs launched in same second have duplicate MapReduce JobIDs. That is about job IDs just coming from the system current time, not 0. But: you can try upgrading your spark version to see if it goes away.

My suggestions

1. make sure your jobs are not writing to the same table simultaneously. Things will get in a mess.
2. grab the most recent version spark you are happy with

I honestly don't know why you get that error with assign, but one way to add a new column to a koalas.DataFrame is to use the standard assignment method [''] like below.
It is important to change the option compute.ops_on_diff_frames to allow operations on different Series/DataFrames.

The error is because of below code.

There is currently no option for this in the spark documentation. There also seem to be differing opinions/standards on the validity of jsons with duplicate key values and how to treat them (SO discussion).

Supplying the schema without the duplicate key field results in a successful load. It takes the value of the last key in the json.

The schema depends on your source file.