How to Convert XML to Parquet Format?
If you have large XML files and are facing issues like slow processing, heavy file size, or difficulty in analyzing data, then converting XML to Parquet format is the best and easiest way for a smooth process. This guide is going to explain the possible and non-technical methods to convert XML to Parquet format using Python Script, Apache Spark, and an automatic solution for hassle free process.
Most of the businesses store data in XML format, which stands for Extensible Markup Language, because it is flexible and readable for machines. But when your XML file becomes larger, it can be slow, bulky, and difficult to manage in any analytics platforms.
That’s where Parquet comes in:
Parquet is one of the best, modern, column-based file formats, which is highly efficient for large data storage and analytics. Multiple platforms use Parquet format, like Apache Hadoop, Apache Spark, and Google BigQuery.
But XML to Parquet conversion is not an easy task, so we have tried to explain all the possible methods with ease one by one.
Manual Techniques for XML to Parquet Conversion
Manual methods can be complex for non-technical users. If you are a technical person who knows coding languages and have Apache Spark application, then go for the manual methods to convert XML to Parquet. Both methods are explained below one by one:
Quick Suggestion to Convert XML to Parquet
If you have no technical knowledge and don’t want to install any heavy application, then you should download the SysTools XML Converter Tool. This is the best solution for large and nested XML files without any limitations. It maintains the original tags and elements during the XML to Parquet conversion process. It has a simple interface that doesn’t require technical knowledge. Download it for free to understand how the tool works before investing to convert XML to Parquet.
Method 1: Using Python Script
This technique works only with a simple XML file structure like:
<employees>
<employee>
<id>1</id>
<name>John</name>
<age>30</age>
<department>Sales</department>
</employee>
<employee>
<id>2</id>
<name>Alice</name>
<age>28</age>
<department>HR</department>
</employee>
</employees>
Now, follow the mentioned steps to convert XML to Parquet:
Step 1: First, you have to install these required packages:
pip install pandas pyarrow
Libraries used:
- pandas → For tabular data handling
- pyarrow → To writea Parquet file
- lXML or XML.etree → To parse XML
Step 2: Simple Python Script (Recommended Method)
Firstly, create a file named convert.py and use this script.
import pandas as pd
# Step 1: Read XML file
df = pd.read_xml(“employees.xml”, xpath=”.//employee”)# Step 2: Convert Data Types (Optional but Recommended)
df[“id”] = df[“id”].astype(int)
df[“age”] = df[“age”].astype(int)# Step 3: Export to Parquet
df.to_parquet(“employees.parquet”, engine=”pyarrow”, index=False)print(“XML successfully converted to Parquet.”)
Step 3: Run the Script
Now follow the script in the same folder where your XML file exists:
python convert.py
And after this, a new file will be created.
employees.parquet
Drawbacks:
- This method is not suitable for large XML files to convert XML to Parquet.
- Your system may crash with high memory usage.
- This technique only supports simple and flat-structured XML files.
- This method cannot handle nested and invalid XML files.
- It contains high chances of script failure due to missing or inconsistent tags.
- Coding knowledge required.
Method 2: Convert XML to Parquet Using Apache Spark Application
Firstly, you need these for a smooth process:
- Java (JDK 8 or above)
- Apache Spark installed
- Spark XML package
Step 1: Run PySpark Session with XML Package
As Spark doesn’t support XML files by default, you must include the Spark XML package when you start Spark.
If running from the command line:
pyspark –packages com.databricks:spark-XML_2.12:0.17.0
This package will allow Spark to read XML file data easily.
Step 2: Basic PySpark Script (Simple XML Structure)
Firstly, create a Python file – spark_XML_to_Parquet.py
from pyspark.sql import SparkSession
# Step 1: Create Spark Session
spark = SparkSession.builder \
.appName(“XML to Parquet Conversion”) \
.getOrCreate()# Step 2: Read XML File
df = spark.read.format(“xml”) \
.option(“rowTag”, “employee”) \
.load(“employees.xml”)# Step 3: View Schema (Optional)
df.printSchema()# Step 4: Write as Parquet
df.write.mode(“overwrite”).parquet(“employees_parquet”)print(“Conversion completed successfully.”)
spark.stop()
Step 3: Run the Script
spark-submit –packages com.databricks:spark-XML_2.12:0.17.0 spark_XML_to_Parquet.py
After the execution, Spark will create:
employees_Parquet/
Finally, inside the folder, you will get the Parquet file.
Drawback of this Manual Technique
- Complex installation and environment setup required.
- Heavy Java and Spark configuration required.
- Basic knowledge about Spark framework.
Best Technique to Convert XML to Parquet
If you don’t want to face any restrictions and don’t have technical knowledge, then you should use the suggested solution. There is no need to install any third-party application; it’s a standalone tool. Let’s understand more features and how it works for better knowledge:
Important Note: This software provides 15+ different saving options including documents and database formats like:
Why Only SysTools XML to Parquet Converter?
- This software supports invalid, complex, simple, and nested XML files easily without limitations.
- This is the only tool that can convert multiple XML files into Parquet format in bulk at the same time.
- It maintains original structure and elements during the XML to Parquet conversion.
- It supports large XML files, including all sizes, without crashing to convert XML to Parquet.
- This XML to Parquet converter works without an internet connection, which makes it safer and more secure.
How to Convert XML to Parquet Format? Tool’s Steps
- Download and start the mentioned software on your system.
- Import your multiple files and folders using the “Add Files / Folders” options.
- Locate the destination of your XML files and use the “Open” icon to load.
- The uploaded file will upload on the panel, and choose the “Next” button to continue the process.
- Choose Parquet” from the “Export” options.
- Check the “Maintain Folder Tree” option to retain the original folder structure.
- Choose any destination to save the output data file using the “Browse” button.
- Hit the “Export” button to convert XML to Parquet.
- After completing the process, a pop-up will appear, and choose the “OK” button.
- Click on the “View Report” button to analyze the conversion process report.
Final Words
This blog has explained the most searched technical queries on the internet on how to convert XML to Parquet format easily using a Python Script and an Apache Spark application manually. But these manual methods have numerous drawbacks, so you can use them for a simple XML file structure. But in case you have nested tags, large, invalid, or complex and multiple XML files, then you should use the suggested automatic XML to Parquet converter by SysTools.
This is the only solution that provides advanced features, not drawbacks like manual techniques. You can download the free demo edition for trial. Or you can contact us through live chat support for smooth XML to Parquet conversion.