The Excel file cannot be read directly using Py-Spark in Databricks so necessary Libraries (com.crealytics.spark.excel) have to be installed in the Cluster to successfully run the Python code.
Step 1
Navigate to the Cluster that will be used to run the Python script under Compute in Databricks.
Step 2
Click on the tab Libraries -> Install new.
Step 3
Select Maven as a Library source and click on Search Packages.
Step 4
Type com.crealytics in the search bar and select Maven Central.
Step 5
Select the com.crealytics.spark.excel package version that matches with the version of Scala (Cluster -> Configuration -> Databricks Runtime Version) in your Cluster.
Step 6
Click Install
Use the following code to load the Excel file:-
// Specify the path to the Excel file
val excelFilePath = "/mnt/<your-mount-name>/path_to_your_excel_file.xlsx"; // Replace with your actual spark file path
// Read the Excel file into a Spark DataFrame
val df = spark.read
.format("com.crealytics.spark.excel")
.option("location", excelFilePath)
.option("useHeader", "true") // Use this option if your Excel file has headers
.load();
Whereas using Pandas Library the following Python code could be used:-
import pandas
excelFilePath = "/mnt/<your-mount-name>/path_to_your_excel_file.xlsx"; # Replace with your actual file path
ef=pandas.ExcelFile(excelFilePath); # Load the Excel file as an object
# Mention the Sheet_Name or use ef.sheet_names to iterate through each sheet data
df=ef.parse(Sheet_Name); # Load the required Excel sheet data
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