databricks

问题 I have a dataframe which has 2 columns: account_id and email_address, now I want to add one more column 'updated_email_address' which i call some function on email_address to get the updated_email_address. here is my code: def update_email(email): print("== email to be updated: " + email) today = datetime.date.today() updated = substring(email, -8, 8) + str(today.strftime('%m')) + str(today.strftime('%d')) + "_updated" return updated df.withColumn('updated_email_address', update_email(df

问题 I have a dataframe which has 2 columns: account_id and email_address, now I want to add one more column 'updated_email_address' which i call some function on email_address to get the updated_email_address. here is my code: def update_email(email): print("== email to be updated: " + email) today = datetime.date.today() updated = substring(email, -8, 8) + str(today.strftime('%m')) + str(today.strftime('%d')) + "_updated" return updated df.withColumn('updated_email_address', update_email(df

问题 I have been using an excellent answer to a question posted on SE here to determine the number of partitions, and the distribution of partitions across a dataframe Need to Know Partitioning Details in Dataframe Spark Can someone help me expand on answers to determine the partition size of dataframe? Thanks 回答1: Tuning the partition size is inevitably, linked to tuning the number of partitions . There're at least 3 factors to consider in this scope: Level of parallelism A "good" high level of

问题 I have been using an excellent answer to a question posted on SE here to determine the number of partitions, and the distribution of partitions across a dataframe Need to Know Partitioning Details in Dataframe Spark Can someone help me expand on answers to determine the partition size of dataframe? Thanks 回答1: Tuning the partition size is inevitably, linked to tuning the number of partitions . There're at least 3 factors to consider in this scope: Level of parallelism A "good" high level of

问题 I have a file with a column containing IDs. Usually, an ID appears only once, but occasionally, they're associated with multiple records. I want to count how many times a given ID appeared, and then split into two separate dfs so I can run different operations on both. One df should be where IDs only appear once, and one should be where IDs appear multiple times. I was able to successfully count the number of instances an ID appeared by grouping on ID and joining the counts back onto the

问题 Closed . This question needs to be more focused. It is not currently accepting answers. Want to improve this question? Update the question so it focuses on one problem only by editing this post. Closed last year . Improve this question Can anyone please explain how Spark Dataframes are better in terms of time taken for execution than Pandas Dataframes. I'm dealing with data with moderate volume and making python function powered transformations For example, I have a column with numbers from 1

问题 Closed . This question needs to be more focused. It is not currently accepting answers. Want to improve this question? Update the question so it focuses on one problem only by editing this post. Closed last year . Improve this question Can anyone please explain how Spark Dataframes are better in terms of time taken for execution than Pandas Dataframes. I'm dealing with data with moderate volume and making python function powered transformations For example, I have a column with numbers from 1

问题 Closed . This question needs to be more focused. It is not currently accepting answers. Want to improve this question? Update the question so it focuses on one problem only by editing this post. Closed last year . Improve this question Can anyone please explain how Spark Dataframes are better in terms of time taken for execution than Pandas Dataframes. I'm dealing with data with moderate volume and making python function powered transformations For example, I have a column with numbers from 1

来源： https://stackoverflow.com/questions/64645788/in-a-scala-notebook-on-apache-spark-databricks-how-do-you-correctly-cast-an-arra

来源： https://stackoverflow.com/questions/64645788/in-a-scala-notebook-on-apache-spark-databricks-how-do-you-correctly-cast-an-arra