Java project that contains static methods that can be called from Snowpark for performing sentiment analysis on text using CoreNLP.
After cloning the project, run mvn package. If all goes well, this will create SentiLyzer-1.0-SNAPSHOT-jar-with-dependencies.jar in the target folder.
Use the Snowflake CLI to upload the jar once it is compiled locally. Follow the instructions here to install the Snowflake CLI.
3.a Start a SnowSQL session at the command line by running snowsql -a <YOUR_SNOWFLAKE_ACCOUNT> -u <YOUR_USER_NAME>
3.b Set the database, schema, and warehouse by running the following command.
use database <YOUR_DATABASE>;
use schema <YOUR_SCHEMA>;
use warehouse <YOUR_WAREHOUSE>;
3.c Upload the jar to Snowflake by running the following command.
put file:///<full-path>/target/SentiLyzer-1.0-SNAPSHOT-jar-with-dependencies.jar
@~/<YOUR_SNOWFLAKE_STAGE_NAME>/
auto_compress = false
overwrite = true;
3.d Create the UDF in Snowflake by running the following command.
create or replace function sentiment_analysis(s varchar)
returns numeric
language java
imports = ('@~/<YOUR_SNOWFLAKE_STAGE_NAME>/SentiLyzer-1.0-SNAPSHOT-jar-with-dependencies.jar')
handler = 'com.dash.analyzer.AnalyzeSentiment.sentiment_analysis';
Use the sentiment_analysis UDF in your SQL queries in Snowflake. For example, to score reviews from AMAZON_REVIEWS table in Snowflake:
SELECT REVIEW, sentiment_analysis(REVIEW) as SCORE
FROM AMAZON_REVIEWS;