PArc | PersonalArchives - Create a WARC file for any URL

finally the problem is that I used a our name for iterated and not the one of the server response is an object, but not an array.

Service.ts

Using pdftotext, I can get the text content of the PDF file :

You can use only spark's builtin functions to get a string containing the list of columns whose value is not unique:

• use countDistinct to determine whether there are several values in a specific column for a specific empID
• save name of the column if count distinct is greater than 2 using when
• iterate over columns and save this iteration into an array using array
• build a string from this array using concat_ws

The complete code is as below:

It's because you're not factoring in the padding: 5px. So, it's calculating 33% + 5px, which means each part is MORE than a third, which means only 2 will fit per row.

You either:

1. • remove the 5px padding with width: calc(33% - 10px)
2. • add the rule: border-box: box-sizing so the padding is part of the 33% instead of being added separately

See:

https://www.w3schools.com/CSSref/css3_pr_box-sizing.asp https://www.w3schools.com/csS/css_padding.asp

I found how to handle this using datatables.net in this JSFiddle But it is not a very nice way to do it as i have to manualy create the rows in the HTML part, also in the JS part. a way to automaticaly create the headers and fill the rows would be better. So to get it working i have to modify the JSON by removing this {"shipments": and the latest }

Youre aligning .parc_name to the top by setting vertical-align:top but youre missing that same styling for .parc_ned so it does not align itself to the top.

By adding vertical-align:top to the .parc_ned selector it moves to the top. I also added matching line-height and display:inline-block to both selectors to make the text inside the elements centered to each other.

The second transformation fails because when you pass a column containing a json string from a dataframe to schema_of_json function Spark can't be sure that each row json string of this column will evaluate to the same schema

To understand why having the same schema for all rows is important, you must acknowledge that main use case for creation of schema_of_json function is to infer schema for from_json function.

from_json transforms a json string to a struct, basically several new columns. And of course all rows in a dataframe should have the same columns. So, you have to ensure that when you use from_json on a dataframe, you pass the same schema to all rows.

At origin, you should have been able to pass a column that is not a literal to schema_of_json, as you can see in ticket SPARK-24642. However, it meant to merge infered schema for each row. For instance, if you have the following dataframe:

I think you are overcomplicating your problem here. Just use the spark inbuilt functions and you should be fine.

I would recommend using spark.read.json function to do your processing. Here, is what i did.

You declare pfd as a pointer to a struct pollfd: