MENU
The data engineer is using Spark's MEMORY_ONLY storage level.
Which indicators should the data engineer look for in the spark UI's Storage tab to signal that a cached table is not performing optimally?
Suggested Answer: C
Get Premium Databricks Certified Data Engineer Professional Questions
as Interactive Web-Based Practice Test or PDF
Real Exam Format
Detailed Explanations
Instant Access
Get Your Practice Test
In the Spark UI's Storage tab, an indicator that a cached table is not performing optimally would be the presence of the _disk annotation in the RDD Block Name. This annotation indicates that some partitions of the cached data have been spilled to disk because there wasn't enough memory to hold them. This is suboptimal because accessing data from disk is much slower than from memory. The goal of caching is to keep data in memory for fast access, and a spill to disk means that this goal is not fully achieved.
45 comments · newest first
FA
Fatima
10 months ago
I think the cached partitions being greater is a good sign sometimes.
AN
Antione
11 months ago
On Heap Memory Usage being high is a red flag for sure.
HE
Henriette
11 months ago
Wait, is it normal for RDD Block Names to show cache failures?
IL
Iluminada
11 months ago
Totally agree, cached partitions should match Spark partitions.
TA
Tandra
11 months ago
Size on Disk should be 0 for MEMORY_ONLY!
RA
Raylene
12 months ago
I practiced a question similar to this, and I think the On Heap Memory Usage being too close to Off Heap Memory could signal potential issues with caching performance.
JO
Joaquin
12 months ago
I vaguely recall something about RDD Block Names showing failures to cache, so that might be a key indicator to look for in the Spark UI.
FL
Flo
12 months ago
I'm not entirely sure, but I feel like having more Cached Partitions than Spark Partitions could mean inefficiencies in how the data is being stored.
KE
Kendra
1 year ago
I think I remember that if the Size on Disk is greater than 0, it might indicate that the data isn't fully cached in memory, which could be a problem.
LA
Laquita
1 year ago
I've got this! The answer is B - the number of Cached Partitions should be less than or equal to the number of Spark Partitions.
TI
Tiffiny
1 year ago
I'm a bit confused by the options. I'll need to double-check the Spark documentation to make sure I understand the correct indicators.
ME
Merri
1 year ago
Okay, let's think this through step-by-step. The key is to identify the signs that the cached table is not performing optimally.
KA
Kati
1 year ago
Hmm, I'm not sure about this one. I'll need to carefully review the Spark UI storage tab to look for the right indicators.
FR
Frank
1 year ago
This question seems pretty straightforward. I think I can handle it.
NO
Norah
1 year ago
This seems like a straightforward question about LUN migration. I'll need to remember the key details about LUN migration and how it's used to move LUNs without disrupting service.
MA
Mabel
1 year ago
This looks like a straightforward question on social engineering attack vectors. I'm confident I can identify the three major ones.
AN
Anissa
2 years ago
I'm no data engineer, but I hear caching is like trying to remember where you left your car keys. If the Spark UI is confused, you know you've got a problem!
PH
Phillip
2 years ago
B) The number of Cached Partitions> the number of Spark Partitions
JE
Jettie
2 years ago
A) Size on Disk is> 0
RA
Raul
2 years ago
I feel like the answer is B. Anything that doesn't match the actual Spark partitions is probably not a good sign.
LI
Lizbeth
2 years ago
Yeah, it's important to keep an eye on those indicators in the Spark UI's Storage tab.
JE
Jerry
2 years ago
I agree, that would definitely be a sign that the cached table is not performing optimally.
FR
Frederica
2 years ago
I think the answer is B. If the number of Cached Partitions is greater than the number of Spark Partitions, it's not good.
LE
Lea
2 years ago
I think C) The RDD Block Name included the '' annotation signaling failure to cache is also a valid indicator of poor performance.
EN
Enola
2 years ago
But if the number of Cached Partitions is greater than the number of Spark Partitions, wouldn't that indicate a performance issue?
LE
Lemuel
2 years ago
I disagree, I believe the correct answer is A) Size on Disk is> 0.
GE
Georgeanna
2 years ago
This is a tough one, but I'm going to go with C. The '' annotation in the RDD Block Name is a clear indication of caching failure.
VA
Valentin
2 years ago
I agree with User1, C) The RDD Block Name included the '' annotation signaling failure to cache seems like the right choice
LA
Lachelle
2 years ago
I'm leaning towards B) The number of Cached Partitions> the number of Spark Partitions
JE
Jenelle
2 years ago
I think it's A) Size on Disk is> 0
LA
Latanya
2 years ago
I'm not sure, but I think it might be B) The number of Cached Partitions> the number of Spark Partitions
HE
Helaine
2 years ago
I disagree, I believe it's C) The RDD Block Name included the '' annotation signaling failure to cache
NE
Nell
2 years ago
I think it's A) Size on Disk is> 0
TH
Thaddeus
2 years ago
Hmm, I'm going with B. If the number of cached partitions is greater than the actual Spark partitions, that's a red flag.
YO
Yolando
2 years ago
Yeah, if the number of cached partitions is more than the Spark partitions, it's not performing optimally.
DA
Darci
2 years ago
I think B is the right indicator to look for.
EN
Enola
2 years ago
I think the answer is B) The number of Cached Partitions> the number of Spark Partitions.
CH
Christoper
2 years ago
D sounds like the right choice to me. If the on-heap and off-heap memory usage are out of balance, that's a sign of suboptimal caching.
MA
Marylin
2 years ago
I think the correct answer is C. The RDD Block Name with the '' annotation signals that the caching was unsuccessful.
SC
Scarlet
2 years ago
D) On Heap Memory Usage is within 75% of off Heap Memory usage
GW
Gwenn
2 years ago
C) The RDD Block Name included the '' annotation signaling failure to cache
MA
Mariko
2 years ago
B) The number of Cached Partitions> the number of Spark Partitions
CL
Clare
2 years ago
A) Size on Disk is> 0
VI
Vivienne
2 years ago
User2
LA
Layla
2 years ago
User1