Hardware Sizing

Hardware required for different sizes of data

Zingg has been built to scale. Performance is dependent on:

• The number of records to be matched.

• The number of fields to be compared against each other.

• The actual number of duplicates.

Here are some performance numbers you can use to determine the appropriate hardware for your data.

• 120k records of examples/febrl120k/test.csv take 5 minutes to run on a 4 core, 10 GB RAM local Spark cluster.

• 5m records of North Carolina Voters take ~4 hours on a 4 core, 10 GB RAM local Spark cluster.

• 9m records with 3 fields - first name, last name, email take 45 minutes to run on AWS m5.24xlarge instance with 96 cores, 384 GB RAM

If you have up to a few million records, it may be easier to run Zingg on a single machine in Spark local mode.