How To Make Spark Nlp Work In Databricks

Setting Up Spark NLP in Databricks

To use Spark NLP in Databricks, you need to set up your cluster correctly and install the necessary libraries. Here’s a step-by-step guide:

1. Create a Cluster: If you don’t already have a Databricks cluster, create one. This will be where you install Spark NLP.
2. Configure Spark Settings: In the Advanced Options section of your cluster settings, add the following configurations to the Spark tab:
   • spark.kryoserializer.buffer.max 2000M
   • spark.serializer org.apache.spark.serializer.KryoSerializer
3. Install Spark NLP Libraries: In the Libraries tab of your cluster, install the following:
   • PyPI: spark-nlp==5.5.3
   • Maven: com.johnsnowlabs.nlp:spark-nlp_2.12:5.5.3
4. Attach Notebook: Once the libraries are installed, you can attach a notebook to your cluster and start using Spark NLP.

Frequently Asked Questions

Q: What is the purpose of using KryoSerializer in Spark NLP?

A: KryoSerializer is used to improve serialization efficiency in Spark, which is crucial for complex data types used in NLP tasks.

Q: Can I use Spark NLP with Databricks SQL warehouses?

A: No, Spark NLP does not integrate with Databricks SQL warehouses.

Q: How do I display HTML content in a Databricks notebook?

A: You can use the displayHTML function in Databricks to display HTML content.

Q: What are the system requirements for running ONNX models with GPU on Databricks?

A: To run ONNX models with GPU on Databricks, you need CUDA 12 and cuDNN 9 installed. Databricks runtimes starting from version 15 support this.

Q: How do I manually upgrade cuDNN on a Databricks cluster?

A: You can upgrade cuDNN by running a script as an init script on your cluster. The script should install cudnn9-cuda-12.

Q: Can I use Spark NLP for Healthcare in Databricks?

A: Yes, Spark NLP for Healthcare is available for use in Databricks. It provides state-of-the-art clinical and biomedical NLP capabilities.

Q: How do I structure my Databricks notebooks effectively?

A: Use markdown headings, include cell titles, and add comments to explain code logic. This makes your notebooks easier to understand and maintain.

Bottom Line

Setting up Spark NLP in Databricks involves creating a cluster, configuring Spark settings, and installing the necessary libraries. With these steps, you can leverage the powerful NLP capabilities of Spark NLP within the Databricks environment.

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