Hardware Sizing
Hardware required for different sizes of data
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Hardware required for different sizes of data
Last updated
Was this helpful?
Was this helpful?
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.