Running SQL queries

Whale also enables users to run queries from command-line, against both plain SQL files as well as within markdown files, enabling notebook-style behavior.

Supported connections: BigQuery, Postgres, Presto, Redshift, Snowflake
Executing SQL files
Whale exposes a direct line into SQLAlchemy against connections defined in ~/.whale/config/connections.yaml through the wh run command.
wh run filename.sql -w warehouse_name
If the -w flag is not given, the first warehouse in your connections.yaml file will be used.
If there are multiple warehouses with the same warehouse_name the credentials from the first matching warehouse_name encountered will be used.
Note: this only works for (a) direct connections to warehouses (not the Hive metastore) and (b) connections where permissions allow for query runs.
Jinja templating
wh run also supports Jinja2 templating -- for more information on how to set this up, see Jinja2 templating.
Saving results as comments
If you'd like to store your results automatically as comments within your .sql file, you can add --!wh-run to any SQL file (on its own line) and any wh run execution will automatically string replace this line with the results of the query execution.
For example, the following sql file
select * from census.newtable limit 1
​
--!wh-run
would, upon execution using wh run, would be overwritten as:
select * from census.newtable limit 1
​
/* results: 2021-01-12 14:42:24.318297
--------------------------------------
   customer_id       date1 test_field
0            1  2019-10-01       None
*/
Running SQL blocks within markdown files
The wh run command can also be used against files with the .md or .markdown extension, to enable more advanced Jupyter-notebook style behavior within your IDE.
Any block (```sql) containing --!wh-run will flag said block will:
1.Flag this block for execution when wh run is called on this file.
2.Upon execution, replace the line containing --!wh-run with a block of results.
This behavior is very similar to the execution within SQL files as shown above, but enables execution of SQL query blocks alongside context written in Markdown.
For instance, the following Markdown file
# My project
​
I've found that we've had some problems with this census table!
​
```sql
select * from census.newtable limit 1
​
--!wh-run
would be overwritten upon execution of `wh run` as:
​
```text
# My project
​
I've found that we've had some problems with this census table!
​
```sql
select * from census.newtable limit 1
​
/* results: 2021-01-12 14:42:24.318297
--------------------------------------
   customer_id       date1 test_field
0            1  2019-10-01       None
*/
For those familiar with Jupyter or R markdown notebooks, this pattern might feel somewhat foreign. Unlike with full-fledged programming languages, there is no need for logic to be transferred between cells in SQL, so we've made the conscious decision to simplify the usage pattern and supporting code by not building out support for execution of individual code blocks except for through explicit inclusion of the `--!wh-run` statement. This has the added benefit of being minimally destructive, only replacing the `--!wh-run` character sequence.
​
### Editor configuration
​
#### Vim
​
Add the following to your `.vimrc` file, and you can run `<Leader>wh` to execute whale files. `<Leader>` is generally `\` or `,`.
​
```text
nmap <Leader>wh :w<CR>:exec '!~/.whale/bin/whale run %'<CR>:e<CR>
Or if installed via Homebrew:
nmap <Leader>wh :w<CR>:exec '!/usr/local/bin/wh run %'<CR>:e<CR>
Vscode
TODO

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Query automation and alerting

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Outline

Executing SQL files

Jinja templating

Saving results as comments

Running SQL blocks within markdown files