MS Excel tin can brandish ane,048,576 rows. While that may seem like a really large number in normal usage, there are plenty of scenarios where that isn't quite enough.

Whether you're looking at log files or large data sets, information technology's piece of cake to come beyond CSV files with millions of rows or enormous text files. Since Excel cannot back up files this large, how exactly do you open them? Allow's find out.

Why Can Normal Text Editors Not Open Really Large Files?

A reckoner has gigabytes of storage, so why can't text editors open large files?

There are two factors at play here. Some applications take a hardcoded limit on how much data they can display. Information technology doesn't matter how much memory your PC has, they just won't use it.

The second issue is RAM. Many text editors do not have a hard limit on the number of rows, but cannot display large files due to memory limitations. They load the entire file into the organisation RAM, so if this memory isn't large enough, the process fails.

Method #one: Using Free Editors

The all-time way to view extremely big text files is to employ… a text editor. Non merely any text editor, but the tools meant for writing code. Such apps can usually handle large files without a hitch and are costless.

Large Text File Viewer is probably the simplest of these applications. It'southward really easy to apply, works fast and has a very depression resource footprint. The only downside? It cannot edit the files. Only if you only want to view large CSV files, this is hands down the best tool for the job.

For editing large text files as well, y'all should endeavor Emacs. Originally created for Unix systems, information technology works perfectly well on Windows too, and can handle big files. Similarly, Neovim and Sublime Text are two lightweight IDEs that can be used to open gigabyte-sized CSV text files.

If all you're looking for is to search for data through large log files, so klogg is only the tool for you. An updating fork of the popular glogg, this application allows you to perform complex search operations through enormous text files with ease. Since computer-generated log files can often have millions of rows, klogg is designed to piece of work with such file sizes without an event.

Method #2: Split Into Multiple Parts

The whole problem with trying to open up large CSV files is that they are too large. But what if you were to split these into multiple smaller files?

This is a popular solution, as it by and large doesn't involve having to larn the interface of a new text editor. Instead, you lot tin utilise one of the many CSV splitters available online to suspension up the large file into a number of easy-to-open up files. Each of these files can so be accessed usually.

However, this isn't the best way to go nigh this. Splitting a large file tin often lead to weird typos or improperly configured files. Moreover, opening each chunk separately prevents you lot from filtering through the whole data at once.

Method #iii: Import Into a Database

Text and .csv files extending to multiple gigabytes are generally big datasets. And then why not simply import them into a database?

SQL is the nearly common database markup linguistic communication used these days. There are many versions of SQL in apply, only the easiest is probably MySQL. And every bit luck would have it, it is possible to convert a CSV file into a MySQL table.

This is past no ways the easiest method of dealing with large CSV files, then we only recommend this if you want to deal with large datasets on a regular basis. If MySQL sounds likewise tough, y'all can always import your .csv files to MS Admission instead.

Method #four: Analyze With Python Libraries

When you're working with a .csv file with millions of rows of data, you're manifestly not going to be able to make much sense of it manually. You lot probably want to filter the data and run specific queries to understand trends.

So why not write Python code to exercise only that?

Once over again, this is not the most user-friendly method. While Python isn't the hardest programming language to learn, it is coding, so it might not be the all-time arroyo for you. Still, if y'all find yourself having to parse through really large CSV files on a daily basis, yous might want to automate the task with some Python code.

Method #five:  With Premium Tools

The text editors nosotros saw in the first method weren't dedicated tools meant for CSV processing. They were general-purpose tools that could be used to work with big .csv files likewise.

Simply what about specialized applications? Are there no apps out there that are created to solve this problem?

There are, actually. CSV Explorer, for case, builds on the very process we described in the concluding 2 methods (SQL database and Python code) to create an app capable of viewing and editing CSV files of any size. Y'all can do everything y'all expect from a spreadsheet tool similar create graphs or filter the data in CSV Explorer.

Another option is UltraEdit. Dissimilar the previous tool, this is meant non but for .csv files but for any type of text file. Information technology can hands handle text and CSV files ranging to a few gigabytes, with an interface like to many of the gratis editors we discussed before.

The merely drawback with these tools is that they are premium applications, requiring you lot to get a paid license to be able to use them. You tin can always endeavour out their free trial versions to bank check out their features, or if yous but have a one-fourth dimension use.

What Is the Best Fashion To Open up Large Text and CSV Files?

In this age of Big Data, information technology's not uncommon to run into text files running into gigabytes, which can exist hard to even view with built-in tools like Notepad or MS Excel. To be able to open such large CSV files, y'all need to download and use a third-party awarding.

If all you desire is to view such files, then Big Text File Viewer is the best choice for you. For really editing them, you tin can try a feature-rich text editor like Emacs, or go for a premium tool like CSV Explorer.

Techniques like splitting the CSV file or importing information technology into a database involve just too many steps. You lot're better off getting a paid license of a dedicated premium tool if yous discover yourself working with huge text files a lot.