Spark-Scala | Spark program with
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kandi X-RAY | Spark-Scala Summary
Spark program with scala:MLlib基本数据类型的使用;MLlib提供的数理统计方法的使用;机器学习算法Demo
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QUESTION
I am trying to write a unit test code for my Spark-Scala notebook using scalatest.funsuite but the notebook with test() is not getting executed in databricks. Could you please let me know how can I run it?
Here is the sample test code for the same.
...ANSWER
Answered 2021-Jun-14 at 15:42You need to explicitly create the object for that test suite & execute it. In IDE you're relying on specific runner, but it doesn't work in the notebook environment.
You can use either the .execute
function of create object (docs):
QUESTION
I have a nested source json file that contains an array of structs. The number of structs varies greatly from row to row and I would like to use Spark (scala) to dynamically create new dataframe columns from the key/values of the struct where the key is the column name and the value is the column value.
Example Minified json record ...ANSWER
Answered 2021-May-10 at 05:47You could do it this way:
QUESTION
I would like to do a "filldown" type operation on a dataframe in order to remove nulls and make sure the last row is a kind of summary row, containing the last known values for each column based on the timestamp
, grouped by the itemId
. As I'm using Azure Synapse Notebooks the language can be Scala, Pyspark, SparkSQL or even c#. However the problem here is that the real solution has up to millions of rows and hundreds of columns, so I need a dynamic solution that can take advantage of Spark. We can provision a big cluster to how to make sure we take good advantage of it?
Sample data:
...ANSWER
Answered 2021-Apr-14 at 15:32For many columns
you could create an expression
as below
QUESTION
I have three files like:
...ANSWER
Answered 2021-Mar-06 at 17:08You can use reduce
to sum up the arrays:
QUESTION
I'm experiencing problem with maven (tried sbt as well, same result) and Google's guava, which I'm new to.
I found a lot of questions of this kind in SO, but none of the solutions worked for me (searched for internal deps using mvn tree | less
, excluded guava from everywhere, deleted my local .m2, reset cache in IntelliJ, tried all af the Guava versions starting from 22.0). no matter what, I keep getting:
ANSWER
Answered 2020-Dec-21 at 13:25the solution was to place guava
to the very beginning of the , remove
hadoop
as an independent dependency, switch to hadoop2 (instead of 3) and Java8 (instead of 11) and add maven-shade-plugin
. the resulting pom.xml:
QUESTION
I have a file with following type of strings:
...ANSWER
Answered 2020-Nov-21 at 15:53The main problem with your current approach is that the second replacement also needs to remove whitespace, otherwise it will only remove digits, but leave behind both letters and spaces. Then, you need an additional step to reintroduce the original spaces in between each character. Assuming you wanted to use a Java-esque approach, you could try:
QUESTION
I have a dataframe as:
...ANSWER
Answered 2020-Nov-19 at 08:13one way to address the irregular size in the column is to tweak the representation.
for example:
QUESTION
I am looking for specifically a flatmap solution to a problem of mocking the data column in a spark-scala dataframe by using data duplicacy technique like 1 to many mapping inside flatmap
My given data is something like this
...ANSWER
Answered 2020-Nov-18 at 04:01I see that you are attempting to generate data with a requirement of re-using values in the ID column.
You can just select the ID column and generate random values and do a union back to your original dataset.
For example:
QUESTION
I have two Spark-Scala dataframes and I need to use one boolean column from one dataframe to filter the second dataframe. Both dataframes have the same number of rows.
In pandas I would so it like this:
...ANSWER
Answered 2020-Sep-08 at 18:00you can zip both DataFrame
s and filter on those tuples.
QUESTION
I use below code in Spark-scala to get the partitioned columns.
...ANSWER
Answered 2020-Oct-17 at 19:18part_cols
in the question is an array of rows. So the first step is to convert it into an array of strings.
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