[GRIFFIN-297] Allow support for additional file based data sources

**What changes were proposed in this pull request?**

The PR extends the current support beyond just Avro and Text for various file based data sources (Parquet, ORC, etc).

 - Allows users to specify additional file based data sources like Parquet, CSV, TSV, ORC etc.
 - Allows data to be read directly from stand-alone files as well as directories present in both local/ distributed file systems.
 - Allows users to specify schema directly through options (useful for CSV/ TSV types).

A sample config looks like,

  "name": "source",
  "baseline": true,
  "connectors": [
      "type": "file",
      "version": "1.7",
      "config": {
        "format": "parquet",
        "options": {
          "k1": "v1",
          "k2": "v2"
        "paths": [

**Does this PR introduce any user-facing change?**

**How was this patch tested?**
Griffin test suite. Some additional unit test has also been added.

Author: chitralverma <chitralverma@gmail.com>

Closes #555 from chitralverma/allow_file_based_batch_connectors.
3 files changed
tree: 0c528cd4c8a6a4cedf48c8485de6d110a9d50479
  1. griffin-doc/
  2. measure/
  3. service/
  4. ui/
  5. .gitignore
  6. .travis.yml
  8. KEYS
  10. merge_pr.py
  11. NOTICE
  12. pom.xml
  13. README.md
  14. scalastyle-config.xml

Apache Griffin

Build Status License: Apache 2.0

The data quality (DQ) is a key criteria for many data consumers like IoT, machine learning etc., however, there is no standard agreement on how to determine “good” data. Apache Griffin is a model-driven data quality service platform where you can examine your data on-demand. It provides a standard process to define data quality measures, executions and reports, allowing those examinations across multiple data systems. When you don't trust your data, or concern that poorly controlled data can negatively impact critical decision, you can utilize Apache Griffin to ensure data quality.

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