What job version(s) produced and consumed dataset version X? As you start a job, Marquez begins to collect the run states, and then associates run states to that run, producing a dataset version when completed.
#Lineage w code code#
So as your code changes the integrations with GitHub GitLab, Marquez applies a straightforward logic to version that dataset. A lot of the time, with a job, the code changes it’s not static.
Marquez introduces the ability to version datasets and jobs.Īs Marquez looks at the linear events and looks at a job, it sees what metadata has changed.
Marquez allows you to search catalogs and give you all the answers quickly. Imagine joining a company, and you want to know some top datasets or some data sets that you should be using for your dashboard or pipeline. Metadata ServiceĪt its core, Marquez is a metadata service. The possibilities are endless! Part 2: Marquez 1. What is the use case for lineage? It truly enhances every use case that it touches. Prefixes in facet names allow the definition of Custom Facets that can be promoted to the spec at a later point.įacets can be used to extend each of these core entities in a variety of ways.
Built around core entities: Datasets, Jobs, and Runsįacets are atomic pieces of metadata identified by a unique name that can be attached to core OpenLineage entities. OpenLineage standardizes how information about lineage is captured across the ecosystem. With OpenLineage, we’re able to unify a lot of this work so that these data collectors can be built once and benefit a whole cohort of tools that need the same information. would have had to build separate integrations with all the different analysis tools and schedules and warehouses and SQL engines and other metadata servers. Providing lineage information to various consumers that require this data.īefore OpenLineage tools like Marquez, Amundsen, etc. Sending lineage information using the OpenLineage specification to various backends. Capturing lineage metadata from the tools that produce datasets and perform data transformations. The OpenLineage architecture was designed to capture real-time data lineage for operational use cases, and work with all kinds of different tools. So OpenLineage observes jobs to capture data lineage as they run (as opposed to attempting to reconstruct it afterward from the information left behind). The best moment to capture context about a dataset is when that dataset is created. PURPOSE: To define an open standard for the collection of lineage metadata from pipelines as they are running. There’s a lot to gain by having the entire industry work together to establish a standard for lineage, and OpenLineage is exactly that: a lingua franca for talking about how data moves across different tools. OpenLineageįirst and foremost, OpenLineage is a community. Practically speaking, data lineage should be something very visual, like a map of your data pipeline that helps you understand how datasets affect one another 5. What is data lineage?ĭata lineage is the set of complex relationships between datasets and jobs in a pipeline. The solution to this challenge is data lineage. It can be difficult to find information such as: Having a fragmented data ecosystem with the potential for organic growth in an organization is beneficial, but it also creates a data “black box.” A healthy data ecosystem in a properly functioning organization looks like a somewhat fragmented, chaotic mess that provides both opportunity and challenge. The result of data democratization (which is otherwise a terrific thing) is fragmentation, as in the picture above. Building a healthy data ecosystemīut it’s not super easy to build a healthy data ecosystem! How do we go about building good data inside of an organization?ĭata availability, freshness, and quality are fundamental capabilities, required as a base layer to achieve higher-order business benefits.Īn organization consistently supplied with good data can begin to methodically optimize and improve its processes, look for anomalies in the data that can lead improvements and better business results.
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