Databricks Community

Hi @xiaojun wang​  please check the blog and let us know if this helps you.https://databricks.com/blog/2015/07/15/introducing-window-functions-in-spark-sql.html

Spark 3 has experimental support for ANSI. Read more here:https://spark.apache.org/docs/3.0.0/sql-ref-ansi-compliance.html

The correct syntax would be: SELECT 'Goal' AS Type, Value FROM table

Hm, seems to work now.

In newer versions of spark it's possible to use ANTI JOIN and SEMI JOIN It looks this way:WITH a AS ( SELECT '1' AS id, 'Super Company' AS name UNION SELECT '2' AS id, 'SUPER COMPANY' AS name ), b AS ( SELECT 'a@b.com' AS user_username, 'Super Co...

There is no offset support yet. Here are a few possible workarounds If you data is all in one partition ( rarely the case ) , you could create a column with monotonically_increasing_id and apply filter conditions. if there are multiple partitions...

import sqlContext.implicits._import org.apache.spark.sql.functions._inputDF.select(   unix_timestamp($"unix_timestamp").alias("unix_timestamp"),   from_utc_timestamp($"unix_timestamp".cast(DataTypes.TimestampType), "UTC").alias("UTC"),   from_utc_tim...

I am trying to store a dataframe as table in databricks and encountering the following error, can someone help? "typeerror: field date: can not merge type <class 'pyspark.sql.types.stringtype'> and <class 'pyspark.sql.types.doubletype'>"

you can try this: df.na.drop(how = "all"), this will remove the row only if all the rows are null or NaN

@cfregly​ : For DataFrames, you can use the following code for using groupBy without aggregations.Df.groupBy(Df["column_name"]).agg({})

@mudassar45@gmail.com as the document describe generic column not yet associated. Please refer the below code. display(peopleDF.select("firstName").filter("firstName = 'An'"))

Hi, I have the opposite issue. When I run and SQL query through the bulk download as per the standard prc fobasx notebook, the first row of data somehow gets attached to the column headers. When I import the csv file into R using read_csv, R thinks ...