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
  • 80m records with 8-10 fields took less than 2 hours on 1 driver(128 GB RAM, 32 cores), 8 workers(224 GB RAM, 64 cores). This is a user-reported stat without any optimization.
If you have up to a few million records, it may be easier to run Zingg on a single machine in Spark local mode.