Zingg
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    • Running On AWS
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    • Ignoring Commonly Occuring Words While Matching
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  • Steps to run zingg on S3
  • Model location

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  1. Data Sources and Sinks

AWS S3

Zingg can use AWS S3 as a source and sink

Steps to run zingg on S3

  • Set a bucket, for example - zingg28032023 and a folder inside it,for example - zingg

  • Create aws access key and export via env vars (ensure that the user with below keys has read/write access to above) export AWS_ACCESS_KEY_ID=<access key id> export AWS_SECRET_ACCESS_KEY=<access key> (if mfa is enabled AWS_SESSION_TOKEN env var would also be needed )

  • Download hadoop-aws-3.1.0.jar and aws-java-sdk-bundle-1.11.271.jar via maven

  • Set above in zingg.conf spark.jars=//hadoop-aws-3.1.0.jar,//aws-java-sdk-bundle-1.11.271.jar

  • Run using below commands

 ./scripts/zingg.sh --phase findTrainingData --properties-file config/zingg.conf  --conf examples/febrl/config.json --zinggDir  s3a://zingg28032023/zingg
 ./scripts/zingg.sh --phase label --properties-file config/zingg.conf  --conf examples/febrl/config.json --zinggDir  s3a://zingg28032023/zingg
 ./scripts/zingg.sh --phase train --properties-file config/zingg.conf  --conf examples/febrl/config.json --zinggDir  s3a://zingg28032023/zingg
 ./scripts/zingg.sh --phase match --properties-file config/zingg.conf  --conf examples/febrl/config.json --zinggDir  s3a://zingg28032023/zingg

Model location

Models etc. would get saved in 
Amazon S3 > Buckets > zingg28032023 > zingg > 100
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Last updated 1 month ago

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