[FEATURE]Table Analysis API

[YANG-DB]

Is your feature request related to a problem?

In some cases the user can benefit from a build-in table analysis API (query) so that it can have a good estimation regarding cost/compute for different operations

What solution would you like?
Flint call /_async_analyze/$tableName would result with the following response:

Based on the statistics provided, here's the summarized information about the table:

- **Table Name**: `otel_traces`
- **Database**: `default`
- **Owner**: `hadoop`
- **Created By**: `Spark 3.3.2-amzn-0`
- **Table Type**: `EXTERNAL`
- **Data Format**: `json`
- **Location**: `s3://flint-data-dp-eu-west-1-beta/oteldemo`

### Statistics

- **Total Size**: 297,027,661,632 bytes (approximately 297 GB)
- **Total Rows**: 5,982,891 rows

### Technical Details

- **Serde Library**: `org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe`
- **InputFormat**: `org.apache.hadoop.mapred.SequenceFileInputFormat`
- **OutputFormat**: `org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat`

implementation process:

• First metadata stats is collected using the next statement: ANALYZE TABLE tableName COMPUTE STATISTICS
• Afterwards the collected data is fetched using the following statements : DESCRIBE EXTENDED tableName

This process can also be collected continuously so that the query engine has updated statistics for query analysis .
The user may be shown this statistics while hovering over the table in the data explorer view

Do you have any additional context?

• https://spark.apache.org/docs/latest/sql-ref-syntax-aux-analyze-table.html

[dai-chen]

Not clear what's the issue. Is existing Analyze and DESC statement in Spark not sufficient?