Member since
03-11-2016
73
Posts
16
Kudos Received
16
Solutions
My Accepted Solutions
Title | Views | Posted |
---|---|---|
1149 | 08-21-2019 06:03 AM | |
35977 | 05-24-2018 07:55 AM | |
4745 | 04-25-2018 08:38 AM | |
6474 | 01-23-2018 09:41 AM | |
2098 | 10-11-2017 09:44 AM |
08-21-2019
06:03 AM
1 Kudo
This might be caused by NIFI-5525. Check for double quotes in your CSV. Either remove them or update NiFi to >=1.8.0.
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09-04-2018
04:41 PM
@RAUI Yes there is another way of achieving this. You can use the method copy() from the FileUtil class and pass your FileSystem object to it to effectively copy your files from the source HDFS location to the target. As with using rename() you will need to ensure you target directory is created before calling copy. FileUtil.copy() has a signature where you provide a source and destination FS and in this case you would provide the same FS object since you are looking to copy files to a different location on the same HDFS. There is also a boolean option to delete the source file after the copy if that fits your use case. Here is a link to the FileUtil API: http://hadoop.apache.org/docs/r2.8.0/api/org/apache/hadoop/fs/FileUtil.html
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01-23-2018
02:01 PM
@Anton P I'm glad it works. I'm not sure how exactly the "fair" ordering policy works inside one queue, but preemption is only for between queues. I assume, that it will try to give resources to the applications/users in the same queue equally, but once a container is running it will not preempt it. If you would like to achieve that, you should consider creating sub-queues.
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09-25-2017
02:54 PM
@gnovak Thank you so much. I was really confused about which version of Python that requires parentheses after print. I thought it was Python2.
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07-06-2017
02:41 AM
how can we identify a job taking more resources than allocation?
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07-04-2017
07:03 AM
Hi, jq can be found in most Linux distributions. If you want to use basic unix commands, maybe try date -d $((1497691710912 / 1000)) Or maybe you can use python, it's also part of every distributions. import json
from datetime import datetime
def timestamp_to_str(timestamp):
return datetime.fromtimestamp(timestamp / 1000).strftime('%Y-%m-%d')
def search(timestamp):
with open('a') as f:
data = json.loads(f.read())
for cluster in data:
cluster['original_timestamp'] = timestamp_to_str(cluster['original_timestamp'])
if cluster['original_timestamp'] == timestamp:
yield cluster
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06-06-2017
01:13 PM
Ok,thank you very much.I thought that in the fact there is a way to remove it,just I don't know。
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05-07-2019
03:35 PM
Unable to update .jar file using command jar uf hadoop-yarn-server-nodemanager-*.jar container-log4j.properties Getting the following error. java.io.IOException: Error in writing existing jar file at sun.tools.jar.Main.run(Main.java:286) at sun.tools.jar.Main.main(Main.java:1288)
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04-24-2017
07:33 AM
@Sami Ahmad I tried your config and the ResourceManager's logs show error: "Illegal capacity of -1.0 for queue root.Support". Support is defined in root.queues, but it's capacity is undefined. If you fixed that (add yarn.scheduler.capacity.root.Support.capacity) the next problem will be, that the sum of the capacities of any queue's child queues must be 100%. In your case, root.Marketing + root.Engineering = 200%. Try the following: yarn.scheduler.capacity.root.Engineering.capacity=40
yarn.scheduler.capacity.root.Marketing.capacity=40
yarn.scheduler.capacity.root.Support.capacity=20
or any other 3 numbers that add up to 100. If you fix this too, your config will be valid:
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02-06-2017
02:42 PM
You can check if the values you configured are actually in use with this command: hdfs getconf -confKey yarn.nodemanager.resource.memory-mb or from the ResourceManager UI: <rm.host>:8088/conf If the values are in sync, you can also check the ResourceManager logs for further information.
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