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A Big Data customer is experiencing failures on a Table input step when running a PDl transformation on AEL Spark against a large Oracle database.
What are two methods to resolve this issue? (Choose two.)
Choose 2 answers
Suggested Answer: A, B
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12 comments · newest first
LU
Lucy
2 months ago
I’m leaning towards A and C. Increasing message buffers might help too.
KA
Kayleigh
2 months ago
Agreed! D is crucial. More driver memory can prevent failures.
KA
Katina
2 months ago
I think B and D are the best options. Loading to HDFS helps with large data.
PR
Princess
2 months ago
Adding Step ID? That sounds unnecessary for this issue.
MI
Mickie
2 months ago
Wait, increasing message buffers? Isn't that just a band-aid fix?
MA
Madalyn
2 months ago
I agree with B, but D seems risky. More memory can lead to other issues.
MA
Matilda
3 months ago
I think A could help too, but not sure it's the best option.
RE
Regenia
3 months ago
Definitely B and D! HDFS helps with large datasets.
KA
Kanisha
3 months ago
The message buffers option seems a bit off to me; I don't recall it being a common solution for this type of issue.
BO
Bong
3 months ago
I think we had a similar practice question about optimizing Spark configurations; increasing memory sounds familiar.
HE
Herminia
3 months ago
I'm not entirely sure, but loading data to HDFS first might help with the input step failures.
NI
Nina
4 months ago
I remember we discussed increasing the Spark driver memory in class; it seems like a good option here.