Member since
07-19-2018
613
Posts
101
Kudos Received
117
Solutions
My Accepted Solutions
Title | Views | Posted |
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4901 | 01-11-2021 05:54 AM | |
3337 | 01-11-2021 05:52 AM | |
8643 | 01-08-2021 05:23 AM | |
8158 | 01-04-2021 04:08 AM | |
36037 | 12-18-2020 05:42 AM |
02-29-2020
06:58 AM
1 Kudo
Assuming you used the same certs, or even if you user different ones; you should be able to click the lock in any SSL based UIs (Ambari, Ranger, Nifi, yarn, grafana, etc) in your browser. This will show you all details of the certs including expiration dates.
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02-24-2020
11:20 PM
1 Kudo
@stevenmatison For the sake of completeness and to confirm your suspicions: With NiFi 1.11.1 parameters also work in the PutEmail-Processor.
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02-19-2020
12:04 AM
1 Kudo
Ok so me and my mate figured it out :). Finally! its like this $.outputs[?(@.name=="EM_CLASSIFICATION")].value
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02-18-2020
08:39 PM
Well, I'm trying to put together a fairly generic service to ingest files. One of the reqs is to be able to strip off any header or trailer lines. Files can come from any number of sources, so I don't think there will be any kind of pattern for a regex.
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02-13-2020
04:19 PM
Hi @vikrant_kumar24,
Looking over your most recent post it appears that @stevenmatison solved your issue. Once you've had a chance to try out the files he's provided, can you confirm by using the Accept as Solution button which can be found at the bottom of his reply so it can be of assistance to others?
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02-12-2020
05:43 AM
Thanks @stevenmatison I am using Parquet format, I tried with ORC not a significant difference, then I changed following setting as follows: Not knowing a lot on the following settings but based on my research. I am not using partitions yet. set hive.cbo.enable=true; set hive.compute.query.using.stats=true; set hive.stats.fetch.column.stats=true; set hive.stats.fetch.partition.stats=true; set hive.vectorized.execution = ture set hive.vectorized.execution.enabled = true also I changed following execution engine set hive.execution.engine = spark I think changing engine to spark made a lot of difference.... Now query is running from 2.48 min to 15 sec I am quite satisfied with current performance but I would sure appreciate other advise for me and for the community. Thanks and appreciate you response. Andy
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02-12-2020
05:02 AM
1 Kudo
@Peruvian81 I would delete only enough to get nifi re-started. Then I would want to go into the flow and look at what has caused it to fill up. This is of course assuming you have enough space in the drive to begin with. Next, I would recommend you should address nifi documented steps for disk configuration, and based on your flow, expand the content repository if necessary and if possible. Last thing to consider: your flow may just need to terminate large flow files when they are completed at the end of the line. If these are held in Q, and no longer needed, they are taking up valuable space.
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02-12-2020
04:57 AM
@AarifAkhter
You need to create permissions within mysql for your ranger user.
An example of this is:
CREATE DATABASE ranger;
CREATE USER 'ranger'@'hdp.cloudera.com' IDENTIFIED BY 'ranger';
GRANT ALL PRIVILEGES ON *.* TO 'ranger'@'hdp.cloudera.com' WITH GRANT OPTION;
FLUSH PRIVILEGES;
where you replace in your hostname for ranger in place of hdp.cloudera.com above:
ip-xxx-xx-xx-xx.ec2.internal
I would also recommend to install using FQDNs (Fully Qualified Domain Names).
Please accept this answer as the solution to close the topic.
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02-04-2020
12:28 PM
@wengelbrecht thank you that is exactly what i needed to see. I am having an issue with the parquet-hadoop-1.10 and need to get a 1.12 version working in NiFi and Hive....
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02-04-2020
09:18 AM
Hi all, Above solution is failing at one scenario, Scenario: if multiple flow files processed at a time and landed in the nifi queue which is used after update query ( i.e. puthiveql which increment processed_file_cnt by one for every flow file ) processor ,then there might be chances of triggering the next flow multiple times and that is wrong. Because we do select processed_file_cnt first and then doing the comparison for processed_file_cnt with input_file_cnt.
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