diff --git a/docs/src/content/docs/guides/column-keys.md b/docs/src/content/docs/guides/column-keys.md index caf944f..a65983f 100644 --- a/docs/src/content/docs/guides/column-keys.md +++ b/docs/src/content/docs/guides/column-keys.md @@ -17,5 +17,5 @@ Column qualifiers in Bigtable can be arbitrary byte arrays. In Smoltable, they n ## Default column The column qualifier can be omitted to access the default column (empty). For instance, -we wanted to have a single column family that stores a title, the column would be accessed +if we wanted to have a single column family that stores a title, the column would be accessed by `title:`. In that case, the `:` can be omitted: `title`. diff --git a/docs/src/content/docs/guides/locality-groups.md b/docs/src/content/docs/guides/locality-groups.md index 4405bff..16ec9db 100644 --- a/docs/src/content/docs/guides/locality-groups.md +++ b/docs/src/content/docs/guides/locality-groups.md @@ -114,7 +114,7 @@ All data is stored in the `_dat_scan-example` partition. Let's ingest some data and query it (body is truncated for brevity): -```json +```bash curl --request POST \ --url http://localhost:9876/v1/table/scan-example/write \ --header 'content-type: application/json' \ @@ -372,7 +372,7 @@ which returns (truncated): } ``` -We get the exact same result, however, we reduce scanned bytes down to 680 bytes, and halved scanned cells, and achieved a read amplification of `1`! +We get the exact same result, however, we reduced scanned bytes down to 680 bytes, and halved scanned cells, achieving a read amplification of `1`! ## Example: Scanning another column family diff --git a/docs/src/content/docs/guides/wide-column-intro.md b/docs/src/content/docs/guides/wide-column-intro.md index 9f802f1..2c9e962 100644 --- a/docs/src/content/docs/guides/wide-column-intro.md +++ b/docs/src/content/docs/guides/wide-column-intro.md @@ -61,7 +61,7 @@ restructure our data: | row key | flight\:FI318 | flight\:FI319 | flight\:EW7033 | flight\:EW7036 | meta\:miles | meta\:model | meta\:operator | | --- | --- | --- | --- | --- | --- | --- | --- | | plane#TF-FIR | 2024-01-25 | 2024-01-25 | | | 51000000 | Boeing 757-256 | Icelandair | -| plane#plane#D-AIQN | | | 2019-10-31 | 2019-10-31 | 52142142 | Airbus A320-211 | Germanwings | +| plane#D-AIQN | | | 2019-10-31 | 2019-10-31 | 52142142 | Airbus A320-211 | Germanwings | We can easily store all data in a single row, using two column families, `flight` and `meta`. Meta contains arbitrary columns of different kind of metadata, while each column inside `flights` is a flight number, with the cell value being the flight data.