Tried to upload a csv on superset installed in centos7. Gives an error message "erro no 13 permission denied on /app/superset/app/
chmod -R incubator-superset gave the necessary permissions recursively to folder-subfolder-files.
Not needed to restart the app as well
Which database are you trying to upload the CSV to? You cannot upload CSVs to the "main" or "examples" databases, to the best of my recollection. You'd have to connect another database of your own.
Once you have a viable database selected, you have to edit the database and check the Allow Csv Upload box, as well as make some changes in the Extra section as per the instructions you see right below that input.
Related
I have a mautic marketing automation installed on my server (I am a beginner)
However i replicated this issue when configuring GeoLite2-City IP lookup
Automatically fetching the IP lookup data failed. Download http://geolite.maxmind.com/download/geoip/database/GeoLite2-City.mmdb.gz, extract if necessary, and upload to /home/ol*****/public_html/mautic4/app/cache/prod/../ip_data/GeoLite2-City.mmdb.
What i attempted
i FTP into the /home/ol****/public_html/mautic4/app/cache/prod/../ip_data/GeoLite2-City.mmdb. directory
uploaded the file (the original GeoLite2-City.mmdb has '0 byte', while the newly added file is about '6000 kb'
However, once i go back into mautic to implement the lookup, the newly added file reverts back to '0byte" and i still cant get the IP lookup configured.
I have also changed the file permission to 0744, but the issue still replicates.
Did you disable the cron job which looks for the file? If not, or if you clicked the button again in the dashboard, it will overwrite the file you manually placed there.
As a side note, the 2.16 release addresses this issue, please take a look at https://www.mautic.org/blog/community/announcing-mautic-2-16/.
Please ensure you take a full backup (files and database) and where possible, run the update at command line to avoid browser timeouts :)
I have a Hive script I'm running in EMR that is creating a partitioned Parquet table in S3 from a ~40GB gzipped CSV file also stored in S3.
The script runs fine for about 4 hours but reaches a point (pretty sure when it is just about done creating the Parquet table) where it errors out. The logs show that the error is:
HiveException: Hive Runtime Error while processing row
caused by:
AmazonS3Exception: Bad Request
There really isn't any more useful information in the logs that I can see. It is reading the CSV file fine from S3 and it creates a couple metadata files in S3 fine as well, so I've confirmed the instance has read/write permissions to the Bucket.
I really can't think of anything else that's going on and I wish there was more info in the logs about what "Bad Request" to S3 that Hive is making. Anyone have any ideas?
BadRequest is a fairly meaningless response from AWS which it sends if there is any reason why it doesn't like the caller. Nobody really knows what's happening.
The troubleshooting docs for the ASF S3A connector list some causes, but they aren't complete, and based on guesswork from what made the message go away.
If you have the request ID which failed, you can submit a support request for amazon to see what they saw on their side.
If it makes you feel any better, I'm seeing it when I try to list exactly one directory in an object store, and I'm co-author of the s3a connector. Like I said "guesswork". Once you find out, add a comment here or, if it's not in the troubleshooting doc, submit a patch to hadoop on the topic.
I am trying to run a demo project for uploading to S3 with Grails 3.
The project in question is this, more specifically the S3 upload is only for the 'Hotel' example at the end.
When I run the project and go to upload the image, I get an updated message but nothing actually happens - there's no inserted url in the dbconsole table.
I think the issue lies with how I am running the project, I am using the command:
grails -Daws.accessKeyId=XXXXX -Daws.secretKey=XXXXX run-app
(where I am supplementing the X's for my keys obviously).
This method of running the project appears to be slightly different to the method shown in the example. I run my project from the command line and I do not use GGTS, just Sublime.
I have tried inserting my AWS keys into the application.yml but I receive an internal server error then.
Can anyone help me out here?
Check your bucket policy in s3. You need to grant permissions to the API user to allow uploads.
I have uploaded a simple 10 row csv file (S3) into AWS ML website. It keeps giving me the error,
"We cannot find any valid records for this datasource."
There are records there and Y variable is continuous (not binary). I am pretty much stuck at this point because there is only 1 button to move forward to build Machine Learning. Does any one know what should I do to fix it? Thanks!
The only way I have been able to upload .csv files to S3 created on my own is by downloading an existing .csv file from my S3 server, modifying the data, uploading it then changing the name in the S3 console.
Could you post the first few lines of contents of the .csv file? I am able to upload my own .csv file along with a schema that I have created and it is working. However, I did have issues in that Amazon ML was unable to create the schema for me.
Also, did you try to save the data in something like Sublime, Notepad++, etc. in order to get a different format? On my mac with Microsoft Excel, the CSV did not work, but when I tried LibreOffice on my Windows, the same file worked perfectly.
I am trying to RAILS_ENV=production run rake paperclip:refresh:thumbnails CLASS=Spree::Image
on my remote server in my current rails app directory, so I can refresh the spree images that I have uploaded in the past.
I am using S3, my bucket is setup correctly as I can see each of my product's images in individual ID folders in my AWS S3 bucket.
But each time I run the above command I get a 'No Such Key' Error when the rake is aborted.
This command runs locally and works fine. (obviously without the RAILS_ENV=production locally)
Ok so I wrote this question to answer it myself. I hope the question makes sense.
For clarity, I had this issue because it was old images (old non existing paths that were associated with an old S3 Key) that I had uploaded with another S3 Key in previous testing on the same rails app. I did this earlier while trying to get S3 to work with my Rails Spree Application.
What I did to solve this was go into my Rails console on my remote server with this command:
$RAILS_ENV=production rails c
I then ordered the list of all Spree:Images them with this:
$y Spree::Image.all(:order => 'attachment_updated_at')
The 'y' is a nice little yaml way of displaying the information of the Spree:Image that's a little more human.
Next I looked at the ID of each Image and noticed that there was a good amount of them with IDs that did not match folders in my AWS S3 bucket.
In my Case the lowest ID number that was in fact a folder in my S3 bucket was '1078' so I ran this:
$Spree::Image.where('id < ?', 1078).destroy_all
This deleted any Spree::Image that had an ID of 1077 or less.
Finally, I closed rails console and ran this on my remote server inside my current rails app directory. (In my case is was /home/deployer/apps/potentialapp/current/)
$RAILS_ENV=production rake paperclip:refresh:thumbnails CLASS=Spree::Image
This reformatted my uploaded images on Spree and everything is now working great.
Hope this saves someone a great big headache. (Oh and empty your cache when you go to test and see if the images have in fact reloaded, almost cried at 4 am last night.)
I solved the same problem using the console and skipping errors (old/broken S3 assets):
Spree::Image.all.each { |i| i.attachment.reprocess! rescue nil }