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In Apache Spark, what is the difference between interweave and explode

I am new to Apache Spark and I am having some hard time to understand the difference between these two functions in Apache Spark.
From what I see in Spark documentation, “explode” is similar to unix command “join”. But what is the difference in detail? What if we have

“A,B,C,D,E” (let’s call them events) as dataset 1
“A,B,E” as dataset 2
A B E (call it matrix1) as dataset 3.

Why do we use “interweave” over “explode” in this situation?
Thanks in advance.

When the dataset has more than one row (event) the spark job needs to operate on the datasets one at a time. So to join or explode, you need to break it into smaller parts and it is simpler to define when there is only one row (event) in a dataset.
Do you get my point?

Unable to start with “sudo modprobe -c”

I am installing a new board, which runs on Debian 5.0.4. As there is no apt-get repository for Debian 5.0.4, I am trying to build my own kernel. This kernel contains intel_agp and nvidia_agp.
My kernel building is done. Installing into system the.config kernel works fine.
When I try to start the kernel with “sudo modprobe -c” I get an error and I do not know why.
The kernel error:

/lib/modules/2.6.32-5-amd64/kernel/drivers/video/nvidia_agp.ko:
FAT

0644bf28c6