In Scala, a package is a technique for grouping together classes, sub-packages, traits, and package objects. In essence, it offers a namespace so that we can place our code in various files and directories. The use of packages makes it simple to maintain our code and avoids name conflicts between members of various packages. To provide access to external or homegrown code by notebooks and processes running on your clusters, you can install a library. The construction of libraries is supported by Python, Java, Scala, and R. one can upload Java, Scala, and Python libraries and point to external packages using the PyPI, Maven, and CRAN repositories.
Installing Scala packages in Databricks
Step 1: To Build a Databricks cluster Follow the below steps.
Step 2: Pick the newly formed cluster.
Step 3: Install New ⇢ Libraries ⇢ Choose Library > Source > “Maven” ⇢ Coordinates Packages for Search ⇢ the Maven Central option ⇢ Look for the necessary package. Example: (GDAL) ⇢ Choose the necessary version (3.0.0) ⇢ Install.
Step 4: One can install a library to give notebooks and processes running on your clusters access to external or custom code. Python, Java, Scala, and R all support the creation of libraries. With the help of the PyPI, Maven, and CRAN repositories, you may upload Java, Scala, and Python libraries and reference external packages.
Step 5: After performing step 1 for the first time, restart the cluster and the Scala packages in Databricks will be successfully installed.