This processor takes in a record set and samples records from the set according to the specified sampling strategy. The available sampling strategies are:

- Interval Sampling

  Select every Nth record based on the value of the Sampling Interval property. For example, if there are 100 records in the set and the Sampling Interval is set to 4, there will be 25 records in the output, namely every 4th record. This performs uniform sampling of the record set so is best suited for record sets that are uniformly distributed. For example a record set representing user information that is uniformly distributed will result in the output records also being uniformly distributed. The outgoing record count is deterministic and is exactly the total number of records divided by the Sampling Interval value.

- Probabilistic Sampling

  Select each record with probability P, an integer percentage specified by the Sampling Probability value. For example, an incoming record set of 100 records with a Sampling Probability value of 20 should have roughly 20 records in the output. Use this when you want to output record sets of roughly the same size (but not exactly) and when you want each record to have the same "chance" to be selected for the output set. As another example, if you send the same flow file into the processor twice, a sampling strategy of Interval Sampling will always produce the same output, where Probabilistic Sampling may output different records (and a different total number of records).

- Reservoir Sampling

  Select K records from a record set having N total values, where K is the value of the Reservoir Size property and each record has an equal probability of being selected (exactly K / N). For example, an incoming record set of 100 records with a Reservoir Size value of 20 should have exactly 20 records in the output, randomly chosen from the input record set. Use this when you want to control the exact number of output records and have each input record have the same probability of being selected. As another example, if you send the same flow file into the processor twice, a sampling strategy of Interval Sampling will always produce the same output (same records and number of records), where Probabilistic Sampling may output different records (and a different total number of records), and Reservoir Sampling may output different records but the same total number of records. Note that the reservoir is kept in-memory, so if the size of the reservoir is very large, it may cause memory issues.

The "Random Seed" property applies to strategies/algorithms that use a pseudorandom random number generator, such as Probabilistic Sampling and Reservoir Sampling. The property is optional but if set will guarantee the same records in a flow file will be selected by the algorithm each time. This is useful for testing flows using non-deterministic algorithms such as Probabilistic Sampling and Reservoir Sampling.