Databricks Community

you can do it by making an api request - convert png to ico paint/api/2.0/clusters/permanent-delete i dont see an option to delete or edit an automated cluster from UI.

Here is a complete example values = [("K1","true","false"),("K2","true","false")] columns = ['Key', 'V1', 'V2'] df = spark.createDataFrame(values, columns) display(df) FILTER df2 = df.filter(df.column2 != "delete") display(df2)

I found that you create a similar comparison plot as what you get from seaborn by using the display(sparkdf) and adding multiple columns to the 'Values' section while creating a 'Scatter plot'. You get to the 'Customize Plot' by clicking on the icon ...

Hi, aromano I know this issue was opened almost a year ago, but I faced the same problem and I was able to solve it. So, I'm sharing the solution in order to help others. Probably, you're using SparkTrials to optimize the model's hyperparameters ...

Hello, Max answer focuses on the CLI. Instead, using the Community Edition Platform, proceed as follows: # You must first delete all files in your folder. 1. import org.apache.hadoop.fs.{Path, FileSystem}  2. dbutils.fs.rm("/FileStore/tables/file.cs...

As suggested by ZAIvR, please use append and provide maxlength while pushing the data. Overwrite may not work with this unless databricks team has fixed the issue

Create temp folder inside output folder. Copy file part-00000* with the file name to output folder. Delete the temp folder. Python code snippet to do the same. fpath=output+'/'+'temp' def file_exists(path): try: dbutils.fs.ls(path) return...

This is a great article. It gave me a lot of useful information. thank you very much download app

Hi @Christian Hofstetter, You can check here for info on the same,https://docs.delta.io/0.4.0/delta-update.html#data-deduplication-when-writing-into-delta-tables

Hi Jigao, OPTIMIZE isn't in the open source delta API, so won't run on your local Spark instance - https://docs.delta.io/latest/api/scala/io/delta/tables/index.html?search=optimize

Hi @ericOnline I also faced the same issue and I eventually found that upgrading the databricks runtime version from my current "5.5 LTS (includes Apache Spark 2.4.3, Scala 2.11)" to "6.5(Scala 2.11,Spark 2.4.5) resolved this issue. Though the offic...