When Does Parquet File Too Large Become an Issue? Reasons & Fixes Explained

We all agree that a Parquet file too large can create many problems for users and data engineers. Even though the Apache Parquet files are known for their capability and efficiency for data handling and analysis, users often come across challenges while dealing with Parquet files or large sizes. In this write-up, we will learn about how this issue can create bigger challenges for the data analysts and how we can resolve the error more efficiently. Let’s first take a look at what causes these files to grow too large and what possible challenges they might create. 

How to Handle the Parquet File Too Big in Size Issue? Optimal Solutions

After learning the common causes and reasons behind the large file size issue, it is now time to take a look at the solutions that will help users resolve this problem without affecting data and structure of the files. 

Method 1: Fix a Parquet File Too Large by Splitting Method

The first method we will discuss is handling the large files by breaking them into smaller chunks. This solution is efficient as it improves the query performance overall and further reduces memory load. 

As recommended, it is better to keep the files between 128 MB and 1 GB in size. 

If we talk about manual approaches for this, they often create issues for the users by compromising the data structure while breaking down the .parquet files into smaller chunks, or offer very limited options for the operation. This is why we suggest using a professional solution like SysTools Parquet Splitter Tool, a utility that offers multiple split options for the user’s convenience and offers the desired results after the process.

Let’s take a look at how this utility works to resolve the large .parquet file issue. 

1. To fix the Parquet file too large problem, install and run the smart software.
2. Browse and add the desired .parquet file in the software.
3. After the files are added, click on the Next Button to begin the split process for large .parquet files.
4. The tool next offers 3 modes to split the files: Split by Rows, Split by Columns, and Split by Size.  Choose a mode as per the requirement.
5. Afterwards, add the value for split size, column name, or row count.
6. Select a destination path to save the resultant files after splitting the files.
7. Lastly, click on the Split Button to resolve the Parquet file too large issue.

These steps can help fix the issue easily without compromising the data integrity or structure of the files throughout the process. The tool also helps users get the desired results afterwards. 

Let’s now take a look at other methods to repair the issue.

Method 2: Implementation of Proper Partitioning in Files

This is another method that helps users deal with big .parquet files. As we learned, one of the reasons for the file growth is improper partitioning of the columns. The method suggests partitioning the dataset depending on the frequency of the columns used, such as:

• Partitioned by Date (year/month/day)
• By Region
• Or By Category 

This method serves many benefits, such as queries don’t have to scan a huge amount of data at once after partitioning. This further improves the processing speed and file organization. Users can carry out safe data analysis after data partitioning in .parquet files too large. Moving on to the next method, let’s see how that helps. 

Method 3: Apply Efficient File Compression

As we read earlier, compression issues can be one of the reasons that can lead to the files growing too large. In this method, we will take a look at some of the modern compression methods that will help with the .parquet file compression to avoid the Parquet file too large issue in Apache Spark. The compression algorithms given below will help the users with efficient file processing:

• Snappy Compression – A widely used compression method that helps reduce file size. 
• Gzip – This compression method offers higher compression but is quite slower in processing. 
• ZSTD – Offers good compression and speed throughout the process.

These compression methods allow users to compress their large, parquet files to a smaller and more manageable size. 

Method 4: Remove Unwanted/ Unnecessary Data

When the Parquet files grow because of the data that are not needed at present, or irrelevant data. It becomes crucial for the users to delete or remove that data from the dataset. Doing so can help users reduce file size conveniently and effectively. Here are the points to remember before writing the dataset to avoid file size growth abruptly:

• Delete or drop unwanted or unused columns from the dataset.
• Filter out and remove duplicate records from the dataset. 
• Find and eliminate irrelevant rows. 

This method will help by reducing the file size after deleting and removing the unwanted data from the dataset, and lastly giving smaller and much cleaner .parquet files as a result.

With the help of the provided methods, users can easily get rid of problems caused by large .parquet files. 

Conclusion

With the help of this guide, we have learned how a Parquet file too large can become a major issue for the users and how it can affect the data analysis process. Furthermore, we have also discussed the common reasons that might lead to the file size growing too much and causing trouble for the users. Lastly, we have listed the optimal solutions to resolve the issue easily and in a hassle-free way.