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Shredding Overview

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Shredding is the process of splitting a Snowplow enriched event into several smaller files, which can be inserted directly into Redshift tables.

A Snowplow enriched event is a 131-column TSV file, produced by Enrich. Each line contains all information about a specific event, including its id, timestamps, custom and derived contexts and much more.

After shredding, the following entities are split out from the original event:

  1. Atomic events. a TSV line very similar to EnrichedEvent but not containing JSON fields (contexts, derived_contexts and unstruct_event). The results will be stored in a path similar to shredded/good/run=2016-11-26-21-48-42/atomic-events/part-00000 and will be available to load via RDB Loader or directly via Redshift COPY.
  2. Contexts. This part consists of the two extracted above JSON fields: contexts and derived_contexts, which are validated (during the enrichment step) self-describing JSONs. But, unlike the usual self-describing JSONs consisting of a schema and a data object, these ones consist of a schema object (like in JSON Schema), the usual data object and a hierarchy object. This hierarchy contains data to later join your contexts’ SQL tables with the atomic.events table. The results will be stored in a path which looks like shredded/good/run=2016-11-26-21-48-42/shredded-types/vendor=com.acme/name=mycontext/format=jsonschema/version=1-0-1/part-00000, where the part files like part-00000 are valid NDJSONs and it will be possible to load them via RDB Loader or directly via Redshift COPY.
  3. Self-describing (unstructured) events. Very much similar to the contexts described above those are the same JSONs with the schema, data and hierarchy fields. The only difference is that there is a one-to-one relation with atomic.events, whereas contexts have many-to-one relations.

Those files end up in S3 and are used to load the data into Redshift tables dedicated to each of the above files under the RDB Loader orchestration.

The whole process could be depicted with the following dataflow diagram.

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