I am trying to read a csv file in cloud datafusion. The csv file uses a multi-character (i.e. ~^~)delimiter. When i try to parse the column using a custom delimiter the tool only considers the first character and splits the file accordingly. I end up with more columns than what is required, plus since the data may have the character even the split is not perfect.
I tries using several patterns not just the one mentioned above, but each time its the same result
How do i parse files where the data is delimited using a multi-char delimiter. Is there a setting that can be used. Is there a separate transform that can be used to parse the file before using the wrangler?
In the assignment i am working on i an limited to use only cloud data fusion as my etl tool
To achieve this, you can use the following directive:
split-to-columns
Related
I want to update a source excel column with a particular string.
My source contains n columns. I need to check where the string apple exists in any one of the columns. If the value exist in any column I need to replace the apple with orange string. And output the excel. How can I do this in ADF?
Note:I cannot use dataflows since we were using a self hosted vm
Excel files has lot of limitations in ADF like it is not supported in the copy activity sink and in Data flow sink as well.
You can raise the feature request for that in ADF.
So, try the above operation with a csv and copy the result to a csv in blob which later you can change it to Excel in your local machine.
To do the operations like above, Data flow can be a better option than doing it with normal activities as Dataflow deals with the transformations.
But Data flow won't support Self hosted linked service.
So, as a workaround first copy the Excel file as csv to Blob storage using copy activity. Create a Blob linked service for that to use in dataflow.
Now follow the below process in Data flow.
Source CSV from Blob:
Derived column transformation:
give the condition for each column case(col1=="apple", "orange", col1)
Sink :
In Sink settings specify as Output to single file.
After Pipeline execution a csv will be generated in the blob. You can convert it to Excel in your local machine.
how can I convert an uploaded CSV to dataframe in foundry using a code workbook? should I use the #transform decorator with spark.read.... (not sure of the exact syntax)?
Thx!!
CSV is a "special format" where Foundry can infer the schema of the CSV and automatically convert it to a dataset. In this example, I uploaded a CSV with hail data from NOAA:
If you hit Edit Schema on the main page, you can use a front end tool to set certain configurations about the CSV (delimiter, column name row, column type etc).
Once it's a dataset, you can import the dataset in Code Workbooks and it should work out of the box.
If you wanted to parse the raw file, I would recommend you use Code Authoring, not Code Workbooks, as it's better suited for production level code, has less overhead and is more efficient for this type of workflow (parsing raw files). If you really wanted to use code workbooks, change the type of your input using the input helper bar, or in the inputs tab.
Once you finish iterating please move this to a Code Authoring repository and repartition your data. File reads at code workbook can substantially slow down your whole code workbook pipeline. Code Authoring offers preview of raw files now, so it's just as fast to develop as using Code Workbooks.
Note: Only imported datasets and persisted datasets can be read in as Python transform inputs. Transforms that are not saved as a dataset cannot be read in as Python transform inputs. Datasets with no schema should be read in as a transform input automatically.
I'm used to use Dataprep to recipe json and csv files from Cloud Storage, but today I tried to ingest a table from BigQuery and could not parametrize.
Is it possible to do that?
Here are some screenshots to illustrate my question:
The prefix that I need
The standard does not work
From Cloud Storage works
In order to ingest a table from BigQuery, you can directly create a Dataset with SQL. I am not sure on what you would like to achieve with the 'Search' input, but it does not accept regular expressions. So, the '*' would not be needed, and just writing 'event_', the interface will filter the matching entries.
We have a ORC file format which are stored in s3 and we want to load the files into AWS Aurora postgres DB .
What we got from internet was :
postgres support csv, txt and other formats not ORC ..
INSERT OVERWRITE DIRECTORY '<Hdfs-Directory-Path>' ROW FORMAT DELIMITED FIELDS TERMINATED BY ',' STORED AS TEXTFILE SELECT * FROM default.foo;
Can any one please help us to find a solution?
This date PostgreSQL on Aurora supports ingestion of data from S3 through the COPY command only from TXT and CSV files.
Since your files are in ORC format, you could convert these tiles in either CSV or TXT and then ingest the data. You could do this very easily with Athena, by simply creating a table for your original data and running a SELECT * FROM table query. As explained in the Working with Query Results, Output Files, and Query History
page, this will automatically generate a CSV file containing the results.
This would not be optimal as you’d pay not only the transform price but also the he storage twice (as original ORC and converted CSV), but it would allow you to convert the data pretty easily.
A better way to do it would instead be to use a service like AWS Glue, that supports S3 as source and that has an Aurora connector. Using this method would give you an actual ETL and even if now you just need the E(xtract) and L(oad), would still leave the door open for any kind of transform you might need in the future.
In this AWS Blog titled How to extract, transform, and load data for analytic processing using AWS Glue (Part 2) they show the opposite flow (Aurora->S3 via Glue), but it should still give you an idea of the process.
I'm trying to import a large dataset into Google Fusion Tables using the csv-import function. The data contains Danish æ-ø-å characters. The original encoding of the data seems to be ANSI (or "windows-1252"). Data uploadet in that encoding is not displayed correctly. I've tried to reencode the various strings in most other relevant encodings (Encoding.(Unicode|ASCII|UTF8) etc.) but nothing seems to please Fusion Tables.
I'm using FileHelpers to generate the csv and I have tried explicitly setting the encoding there too, but to no avail.
UTF 8 should work. I had uploaded this table as a test: http://www.google.com/fusiontables/DataSource?dsrcid=276537