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HDFS is a natural solution for the global access from each spark node, and HDFS is usually supported in spark cluster, that's why we leverage it by default.
Change sparkProperties. I think a complete file path would be better, I'm not sure what's the relative path it should be, relative for the jar package or for the spark worker, maybe for the latter.
We uploaded griffin-measure. The Spark Job submit works. In the Griffin UI it shows successful. But in the Livy logs it shows error code and also do not shows any metrics.
Also one more observation, which could be the cause of the problem. It's regarding hive-stite. Last hurdle. Please validate my understanding.
The Graffin-measure. I did configure ConsoleSink. I may sound little silly, my problem is I am not able to validate whether my integration is working or not.
One last thing. Gaurav i am looking at doing the same thing you tried are you willing to open up the implementation in github?
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Dashboard … Apache Griffin 1. Design Docs 1. Jira links. Created by William Guo , last modified by Lionel Liu on Jan 12, Purpose Griffin DSL is designed for DQ measurement, as a SQL-like language, trying to describe the DQ domain request.
Including kinds of measurement types: accuracy profiling uniqueness timeliness Including kinds of data source types: batch hive avro Basically, to calculate accuracy metrics, users only need to provide comparison rule like where clause source.
SELECT source. NOT source. Optional having clause could be following. No labels. Permalink Jan 11, Delete comments. Lionel Liu. Hi Neil, We don't do any other optimization for accuracy now, just translate it as On clause in spark sql, that works good, as spark sql has some optimization when join with an On clause.
About the sql translation, you can just refer to the contents in this document: For example, the dsl rule is " source. Thanks, Lionel, Liu.
Permalink Jan 12, Delete comments. Source data will be ingested into Apache Griffin computing cluster and Apache Griffin will kick off data quality measurement based on data quality requirements.
Apache Griffin provides front tier for user to easily onboard any new data quality requirement into Apache Griffin platform and write comprehensive logic to define their data quality.
Toggle navigation. Apache Griffin Big Data Quality Solution For Batch and Streaming. GET STARTED. ABOUT APACHE GRIFFIN Apache Griffin is an open source Data Quality solution for Big Data, which supports both batch and streaming mode.
Getting Started Quick Start Quick Start Chinese Version Streaming Use Cases Profiling Use Cases FAQ Community Conference Development Contribution Contributors Download Latest version Archived Need Help?
Streaming Use Cases User Story Say we have two streaming data sets in different kafka topics source, target , we need to know what is the data quality for target data set, based on source data set.
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