I need to restore a lot of object from aws s3 glacier deep archive. So i try to use a s3 batch jobs. For that i use a python code to create a manifest as a csv with to columns Bucket,Key.
But my first issue : some Key contain a comma so the job failed.
To solve (partialy) this issue i just cut the csv file to keep only the first two columns hoping that there are not many files involved.
But now i have another issue:
ErrorMessage: Task target couldn't be URL decoded
Any Idea ?
As mentioned on https://docs.aws.amazon.com/AmazonS3/latest/userguide/batch-ops-create-job.html#specify-batchjob-manifest, the manifest CSV file must be URL encoded. The , character in a key name gets converted to %2C with URL encoding so the resulting file will be valid CSV even with commas in the key name
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I have a flow where I am extracting data from the database, converting the Avro to the CSV format and pushing the CSV in an s3 bucket which has subfolder in it. My S3 structure is like the following:
As you can see in the above screenshot my files are going into a blank folder(highlighted by red) instead of going inside a subfolder called 'Thermal'. Please see my PutS3Object settings:
The final s3 path I want my files to go into is: export-csv-vehicle-telemetry/vin11/Thermal
What settings should I change in my processor so the file goes directly inside the 'Thermal' folder?
Use Bucket name as: export-csv-vehicle-telemetry/vin15/Thermal instead of export-csv-vehicle-telemetry/vin15/Thermal/
The extra slash at the end is not required while specifying bucket names.
BTW, Your image shows vin11 directory instead of vin15. Check if that is correct.
I have a nested json as my source file in S3 and I am trying to copy this file into redshift.
My issues with this are as follows,
I use MAXERROR - I need to skip certain errors because the source file is missing certain fields in some cases and has them in other
I use a JSONPATH file - to pick the fields that I need to copy to redshift
All the columns in the table are varchar
Obviously, since I am using maxerror the copy command executes successfully but the table has 0 records. Here is my copy command
COPY public.table(col1,col2,col3,col4,col5,col6)
from 's3://bucket/filename'
credentials 'redshift'
format as JSON 'jsonpathfile.json'
timeformat 'YYYY-MM-DDTHH:MI:SS'
EMPTYASNULL ACCEPTANYDATE ACCEPTINVCHARS TRUNCATECOLUMNS maxerror 100 ;
If I check into stl_load_errors it keeps saying
Invalid JSONPath format: Member is not an object.
Does this mean the copy command is not able to find even one object that fits the jsonpath file?
Which is definitely not true. I inferred the schema of the input file to design the jsonpath file.
Here is an example from COPY Examples - Amazon Redshift:
copy category
from 's3://mybucket/category_object_paths.json'
iam_role 'arn:aws:iam::0123456789012:role/MyRedshiftRole'
json 's3://mybucket/category_jsonpath.json';
The path to the jsonpath file is specified fully, whereas your example just refers to the filename.
Try specifying the full path starting with s3:// and see whether that helps.
I am trying to generate a file from a Dataframe that I have created in AWS-Glue, I am trying to give it a specific name, I see most answers on stack overflow actually uses Filesystem modules, but here this particular csv file is generated in S3, also I want to give the file a name while generating it, and not rename it after it is generated, is there any way to do that?
I have tried using df.save(s3:://PATH/filename.csv) which actually generates a new directory in S3 named filename.csv and then generates part-*.csv inside that directory
df.repartition(1).write.mode('append').format('csv').save('s3://PATH').option("header", "true")
I am trying to load data which is stored in .gz format in S3 to PostgreSQL server using Datastage. I am using the ODBC connector on the target (database) side. I am able to load uncompressed data from S3 to PostgreSQL but no luck with compressed data so far. I have tried the Expand Stage but it's not helping or I am not doing the right thing. Without the "Expand" the data is coming but it is trying to read the compressed data, while doing so it fails and throws an error:
Amazon_S3_0,1: com.ascential.e2.common.CC_Exception: Failed to initialize the parser: The row delimiter was not found within the first 132 bytes of the file. Ensure that the Row delimiter property matches the row delimiter of the file.
at com.ibm.iis.cc.cloud.CloudLogger.createCCException (CloudLogger.java: 196)
at com.ibm.iis.cc.cloud.CloudStage.processReadAndParse (CloudStage.java: 1591)
at com.ibm.iis.cc.cloud.CloudStage.process (CloudStage.java: 680)
at com.ibm.is.cc.javastage.connector.CC_JavaAdapter.run (CC_JavaAdapter.java: 443)
Amazon_S3_0,1: Failed to initialize the parser: The row delimiter was not found within the first 132 bytes of the file. Ensure that the Row delimiter property matches the row delimiter of the file. (com.ibm.iis.cc.cloud.CloudLogger::createCCException, file CloudLogger.java, line 196)
If someone has come across this, please share your valuable inputs.
I have 8Gb table in BigQuery that I'm trying to export to Google Cloud Storage (GCS). If I specify url as it is, I'm getting an error
Errors:
Table gs://***.large_file.json too large to be exported to a single file. Specify a uri including a * to shard export. See 'Exporting data into one or more files' in https://cloud.google.com/bigquery/docs/exporting-data. (error code: invalid)
Okay... I'm specifying * in a file name, but it exports it in 2 files: one 7.13Gb and one ~150Mb.
UPD. I thought I should get about 8 files, 1Gb each? Am I wrong? Or what am I doing wrong?
P.S. I tried this in WebUI mode as well as using Java library.
For files of certain size or larger, BigQuery will export to multiple GCS files - that's why it asks for the "*" glob.
Once you have multiple files in GCS, you can join them into 1 with the compose operation:
gsutil compose gs://bucket/obj1 [gs://bucket/obj2 ...] gs://bucket/composite
https://cloud.google.com/storage/docs/gsutil/commands/compose
To export it to GCP you have to go to the table and click EXPORT > Export to GCS.
This opens the following screen
In Select GCS location you define the bucket, the folder and the file.
For instances, you have a bucket named daria_bucket (Use only lowercase letters, numbers, hyphens (-), and underscores (_). Dots (.) may be used to form a valid domain name.) and want to save the file(s) in the root of the bucket with the name test, then you write (in Select GCS location)
daria_bucket/test.csv
Because the file is too big, you're getting an error. To fix it, you'll have to break it down into more files using wildcard. So, you'll need to add *, just like that
daria_bucket/test*.csv
This is going to store, inside of the bucket daria_bucket, all the data extracted from the table in more than one file named test000000000000, test000000000001, test000000000002, ... testX.
In my case (more than 1 year after you've asked the question), using a random table of 1,25 GBs, got 16 files with 80,3 MBs each.