add documentation article

docs/practical-examples-and-applications/operating-system-as-a-data-source.md

@@ -18,15 +18,15 @@ SELECT
     ProcessName,
     Directory,
     FileName
-FROM #os.processes() where ProcessName like '%Musoq%'
+FROM #os.processes() WHERE ProcessName LIKE '%Musoq%'
 ```
 
 ## Finding `.cfg` and `.tmp` Files in Downloads
 
-This query retrieves the file size (`Length`) and the full path (`FullName`) of all files located in the `Downloads` directory of the user `{USER}` that have either a `.cfg` or `.tmp` extension. It searches through all the subdirectories (`true` parameter indicates recursive search) within the specified path for files matching the criteria.
+This query retrieves the file size (`Length`) and the full path (`FullPath`) of all files located in the `Downloads` directory of the user `{USER}` that have either a `.cfg` or `.tmp` extension. It searches through all the subdirectories (`true` parameter indicates recursive search) within the specified path for files matching the criteria.
 
 ```sql
-SELECT Length, FullName FROM #os.files('C:\Users\{USER}\Downloads', true) WHERE FullName LIKE '%.cfg' OR FullName LIKE '%.tmp'
+SELECT Length, FullPath FROM #os.files('C:\Users\{USER}\Downloads', true) WHERE FullPath LIKE '%.cfg' OR FullPath LIKE '%.tmp'
 ```
 
 ## Listing Non-empty Files
@@ -55,10 +55,10 @@ SELECT Name FROM #os.files('C:\Users\{USER}\Downloads', true) skip 5 take 5
 
 ## Finding CSV Files Containing 'Frames' Word in File Name
 
-This query searches for `.csv` files that contain the word 'Frames' within their full path (`FullName`) in the `Downloads` directory of the user `{USER}`. It leverages the `rlike` operator for regex pattern matching to filter files. The `true` parameter ensures that the search is conducted recursively through all subdirectories within the specified path, targeting only those `.csv` files whose names include 'Frames'.
+This query searches for `.csv` files that contain the word 'Frames' within their full path (`FullPath`) in the `Downloads` directory of the user `{USER}`. It leverages the `rlike` operator for regex pattern matching to filter files. The `true` parameter ensures that the search is conducted recursively through all subdirectories within the specified path, targeting only those `.csv` files whose names include 'Frames'.
 
 ```sql
-SELECT Name FROM #os.files('C:\Users\{USER}\Downloads', true) WHERE FullName rlike '.*Frames.*.csv'
+SELECT Name FROM #os.files('C:\Users\{USER}\Downloads', true) WHERE FullPath rlike '.*Frames.*.csv'
 ```
 
 ## Filtering `.tmp` and `.cfg` Files by Size
@@ -67,10 +67,21 @@ This query selects the names (`Name`) of files within the `Downloads` directory
 
 ## Combining JPG Files from Two Folders
 
-This query aggregates the full paths (`FullName`) of `.jpg` files from two specific locations: `Folder1` and `Folder2` within the user `{USER}`'s directory. It uses the `UNION ALL` operation to combine the results from both folders into a single list, including duplicates if they exist. The `true` parameter for each `#os.files` function call ensures that the search includes all subdirectories within both specified paths, targeting `.jpg` files exclusively.
+This query aggregates the full paths (`FullPath`) of `.jpg` files from two specific locations: `Folder1` and `Folder2` within the user `{USER}`'s directory. It uses the `UNION ALL` operation to combine the results from both folders into a single list, including duplicates if they exist. The `true` parameter for each `#os.files` function call ensures that the search includes all subdirectories within both specified paths, targeting `.jpg` files exclusively.
 
 ```sql
-SELECT FullName FROM #os.files('C:\Users\{USER}\Folder1', true) WHERE Name LIKE '%.jpg'
-UNION ALL (FullName)
-SELECT FullName FROM #os.files('C:\Users\{USER}\Folder2', true) WHERE Name LIKE '%.jpg'
+SELECT FullPath FROM #os.files('C:\Users\{USER}\Folder1', true) WHERE Name LIKE '%.jpg'
+UNION ALL (FullPath)
+SELECT FullPath FROM #os.files('C:\Users\{USER}\Folder2', true) WHERE Name LIKE '%.jpg'
+```
+
+or you can use cross apply operator:
+
+```sql
+SELECT
+    f.DirectoryName,
+    f.FileName
+FROM #os.directories('C:\Users\{USER}', false) d
+CROSS APPLY #os.files(d.FullName, true) f
+WHERE d.Name IN ('Folder1', 'Folder2')
 ```

docs/practical-examples-and-applications/turning-csv-into-json.md

@@ -0,0 +1,60 @@
+---
+title: Turning CSV into JSON
+layout: default
+parent: Practical Examples and Applications
+nav_order: 8
+---
+
+# Converting CSV to JSON with Musoq - Quick Guide
+
+This guide shows you how to convert CSV files to JSON using Musoq, with special attention to creating structured JSON objects.
+
+## Basic Table View
+
+To view your CSV data in table format, use this command:
+
+```powershell
+./Musoq.exe run query "select * from #separatedvalues.comma('cities.csv', true, 0)"
+```
+
+You'll see your data in a clear table format:
+
+```cli
+┌────────┬──────────┬────────────────┬──────────┬─────────────┬─────────┬───────────┬───────────────────┐
+│ cityId │ cityName │ cityPopulation │ cityArea │ postOffices │ schools │ isCapitol │ isVoivodeshipCity │
+├────────┼──────────┼────────────────┼──────────┼─────────────┼─────────┼───────────┼───────────────────┤
+│ 1      │ Warsaw   │ 1793579        │ 517.24   │ 218         │ 456     │ true      │ true              │
+│ 2      │ Krakow   │ 779115         │ 326.85   │ 156         │ 324     │ false     │ true              │
+│ 3      │ Lodz     │ 679941         │ 293.25   │ 98          │ 278     │ false     │ true              │
+│ 4      │ Zakopane │ 27000          │ 84.23    │ 12          │ 15      │ false     │ false             │
+│ 5      │ Gdansk   │ 470907         │ 262.58   │ 87          │ 198     │ false     │ true              │
+└────────┴──────────┴────────────────┴──────────┴─────────────┴─────────┴───────────┴───────────────────┘
+```
+
+## Simple JSON Output
+
+To convert the same data to flat JSON, add the --format json flag:
+
+```powershell
+./Musoq.exe run query "select * from #separatedvalues.comma('cities.csv', true, 0)" --format json
+```
+
+This produces:
+
+```json
+[{"cityId":"1","cityName":"Warsaw","cityPopulation":"1793579","cityArea":"517.24","postOffices":"218","schools":"456","isCapitol":"true","isVoivodeshipCity":"true"},{"cityId":"2","cityName":"Krakow","cityPopulation":"779115","cityArea":"326.85","postOffices":"156","schools":"324","isCapitol":"false","isVoivodeshipCity":"true"},{"cityId":"3","cityName":"Lodz","cityPopulation":"679941","cityArea":"293.25","postOffices":"98","schools":"278","isCapitol":"false","isVoivodeshipCity":"true"},{"cityId":"4","cityName":"Zakopane","cityPopulation":"27000","cityArea":"84.23","postOffices":"12","schools":"15","isCapitol":"false","isVoivodeshipCity":"false"},{"cityId":"5","cityName":"Gdansk","cityPopulation":"470907","cityArea":"262.58","postOffices":"87","schools":"198","isCapitol":"false","isVoivodeshipCity":"true"}]
+```
+
+## Nested JSON Output
+
+The interpreted_json format allows you to treat column headers as a hierarchy of a JSON object and thus, interpret it to create complex objects. Here's how to use it:
+
+```powershell
+./Musoq.exe run query "select cityId as [city.id], cityName as [city.name], cityPopulation as [city.features.population], cityArea as [city.features.area], postOffices as [city.features.postOffices], schools as [city.features.schools], isCapitol as [city.features.isCapitol], isVoivodeshipCity as [city.features.isVoivodeship] from #separatedvalues.comma('cities.csv', true, 0)" --format interpreted_json
+```
+
+This creates a structured JSON output:
+
+```json
+[{"city":{"id":1,"name":"Warsaw","features":{"population":1793579,"area":517.24,"postOffices":218,"schools":456,"isCapitol":true,"isVoivodeship":true}}},{"city":{"id":2,"name":"Krakow","features":{"population":779115,"area":326.85,"postOffices":156,"schools":324,"isCapitol":false,"isVoivodeship":true}}},{"city":{"id":3,"name":"Lodz","features":{"population":679941,"area":293.25,"postOffices":98,"schools":278,"isCapitol":false,"isVoivodeship":true}}},{"city":{"id":4,"name":"Zakopane","features":{"population":27000,"area":84.23,"postOffices":12,"schools":15,"isCapitol":false,"isVoivodeship":false}}},{"city":{"id":5,"name":"Gdansk","features":{"population":470907,"area":262.58,"postOffices":87,"schools":198,"isCapitol":false,"isVoivodeship":true}}}]
+```