This repository contains schemas for Mozilla's data ingestion pipeline and data lake outputs.
The JSON schemas are used to validate incoming submissions at ingestion time.
The RapidJSON library is used for
JSON Schema Validation. This has implications for what kinds of string patterns
are supported, see the Conformance
section in the linked document for further
details.
To learn more about writing JSON Schemas, Understanding JSON Schema is a great resource.
The Parquet-MR schemas are used for direct to parquet output; some examples of Parquet-MR schemas can be found here: Parquet Schema Examples
- Create the JSON Schema in the
templates
directory first. Make use of common schema components from thetemplates/include
directory where possible, including things like the telemetryenvironment
,clientId
,application
block, or UUID patterns. The filename should betemplates/<namespace>/<doctype>/<doctype>.<version>.schema.json
. - If the data will be saved in parquet form, also add a Parquet-MR schema at
templates/<namespace>/<doctype>/<doctype>.<version>.parquetmr.txt
. - Build the rendered schemas using the instructions below, and check those artifacts (in the
schemas
directory) in to the git repo as well. See the rationale for this in the "Notes" section below. - Add one or more example JSON documents to the
validation
directory. - Run the tests (either via Docker or directly) using the instructions below.
- Once all tests pass, submit a PR to the github repository against the
dev
branch.
- CMake (3.0+) - http://cmake.org/cmake/resources/software.html
- jq (1.5+) - https://github.com/stedolan/jq
git clone https://github.com/mozilla-services/mozilla-pipeline-schemas.git
cd mozilla-pipeline-schemas
mkdir release
cd release
cmake .. # this is the build process (the schemas are built with cmake templates)
The tests expect example pings to be in the validation/<namespace>/
subdirectory, with files named
in the form <ping type>.<version>.<test name>.pass.json
for documents expected to be valid, or
<ping type>.<version>.<test name>.fail.json
for documents expected to fail validation.
The test name
should match the pattern [0-9a-zA-Z_]+
To run the tests:
# build the container with the pipeline schemas
docker build -t mps .
# run the tests
docker run mps
Follow the CMake Build Instructions above, then:
cpack -G TGZ # (DEB|RPM|ZIP)
# Integration Tests (run on schema-test EC2 instance)
# If running locally
# The following RPM's must be installed:
# luasandbox, hindsight, luasandbox-lfs, luasandbox-lpeg, luasandbox-rjson, luasandbox-cjson, luasandbox-parquet
# The following external libraries must be installed
# parquet-cpp
make # this sets up the tests in the release directory
ctest -V -C hindsight # loads all the schemas and tests the inputs in the validation directory against them
- The master branch is the current release and is considered stable at all times.
- New versions can be released as frequently as every two weeks (our sprint cycle). The only exception would be for a high priority patch.
- New releases occur the day after the sprint finishes.
- The version in the dev branch is updated
- The changes are merged into master
- A new tag is created
- All pull requests must be made against the
dev
branch, direct commits tomaster
are not permitted. - All non trivial contributions should start with an issue being filed (if it is a new feature please propose your design/approach before doing any work as not all feature requests are accepted).
All schemas are generated from the 'templates' directory and written into the 'schemas' directory (i.e., the artifacts are generated/saved back into the repository) and validated against the draft 4 schema a copy of which resides in the 'tests' directory. The reason for this is twofold:
- It lets us easily see and refer to complete schemas as they are actually used. This means that the schemas can be referenced directly in bugs and such, as well as being fetched directly from the repo for testing other schema consumers (test being important here, as any production use should be using the installable packages).
- It gives us a changelog for each schema, rather than having to reason about changes to templated external pieces and when/how that impacted a given doctype's schema over time. This means that it should be easy to look back in time for the provenance of different parts of the schema for each doctype.