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update the tutorials for 1.0
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Travis Turner
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1 changed files with 97 additions and 69 deletions
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@ -407,37 +407,65 @@ curl localhost:10101/index/patients \
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-X POST
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```
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``` response
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{}
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{"success":true}
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```
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In addition to storing rows of bits, a frame can also contain fields that store integer values. The next step creates three fields (`age`, `weight`, `tcells`) in the `measurements` frame.
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In addition to storing rows of bits, a frame can also contain fields that store integer values. The next steps creates three fields (`age`, `weight`, `tcells`) in the `measurements` frame.
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``` request
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curl localhost:10101/index/patients/frame/measurements \
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curl localhost:10101/index/patients/field/age \
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-X POST \
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-d '{"options":{
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"fields": [
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{"name": "age", "type": "int", "min": 0, "max": 120},
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{"name": "weight", "type": "int", "min": 0, "max": 500},
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{"name": "tcells", "type": "int", "min": 0, "max": 2000}
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]
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}}'
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-d '{"options":{"type": "int", "min": 0, "max": 120}}'
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```
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``` response
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{}
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{"success":true}
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```
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If you need to, you can add fields to an existing frame by posting to the [Create Field endpoint](../api-reference/#create-field).
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``` request
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curl localhost:10101/index/patients/field/weight \
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-X POST \
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-d '{"options":{"type": "int", "min": 0, "max": 500}}'
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```
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``` response
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{"success":true}
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```
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``` request
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curl localhost:10101/index/patients/field/tcells \
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-X POST \
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-d '{"options":{"type": "int", "min": 0, "max": 2000}}'
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```
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``` response
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{"success":true}
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```
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Next, let's populate our fields with data. There are two ways to get data into fields: use the `SetFieldValue()` PQL function to set fields individually, or use the `pilosa import` command to import many values at once. First, let's set some field data using PQL.
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This query sets the age, weight, and t-cell count for the patient with ID `1` in our system:
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The following queries set the age, weight, and t-cell count for the patient with ID `1` in our system:
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``` request
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curl localhost:10101/index/patients/query \
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-X POST \
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-d 'SetFieldValue(col=1, frame="measurements", age=34, weight=128, tcells=1145)'
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-d 'Set(1, age=34)'
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```
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``` response
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{"results":[null]}
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{"results":[true]}
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```
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``` request
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curl localhost:10101/index/patients/query \
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-X POST \
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-d 'Set(1, weight=128)'
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```
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``` response
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{"results":[true]}
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```
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``` request
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curl localhost:10101/index/patients/query \
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-X POST \
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-d 'Set(1, tcells=1145)'
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```
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``` response
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{"results":[true]}
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```
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In the case where we need to load a lot of data at once, we can use the `pilosa import` command. This method lets us import data into Pilosa from a CSV file.
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@ -454,7 +482,7 @@ Assuming we have a file called `ages.csv` that is structured like this:
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8,33
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9,63
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```
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where the first column of the CSV represents the patient `ID` and the second column represents the patient's`age`, then we can import the data into our `age` field by running this command:
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where the first column of the CSV represents the patient `ID` and the second column represents the patient's `age`, then we can import the data into our `age` field by running this command:
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```
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pilosa import -i patients -f measurements --field age ages.csv
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```
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@ -465,10 +493,10 @@ In order to find all patients over the age of 40, then simply run a `Range` quer
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``` request
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curl localhost:10101/index/patients/query \
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-X POST \
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-d 'Range(frame="measurements", age > 40)'
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-d 'Range(age > 40)'
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```
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``` response
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{"results":[{"attrs":{},"bits":[2,6,9]}]}
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{"results":[{"attrs":{},"columns":[2,6,9]}]}
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```
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You can find a list of supported range operators in the [Range Query](../query-language/#range-bsi) documentation.
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@ -477,21 +505,21 @@ To find the average age of all patients, run a `Sum` query:
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``` request
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curl localhost:10101/index/patients/query \
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-X POST \
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-d 'Sum(frame="measurements", field="age")'
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-d 'Sum(field="age")'
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```
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``` response
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{"results":[{"sum":377,"count":9}]}
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{"results":[{"value":377,"count":9}]}
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```
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The results you get from the `Sum` query contain the `sum` of all values as well as the `count` of columns with a value. To get the average you can just divide `sum` by `count`.
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The results you get from the `Sum` query contain the sum of all values as well as the `count` of columns with a value. To get the average you can just divide `value` by `count`.
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You can also provide a filter to the `Sum()` function to find the average age of all patients over 40.
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``` request
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curl localhost:10101/index/patients/query \
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-X POST \
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-d 'Sum(Range(frame="measurements", age > 40), frame="measurements", field="age")'
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-d 'Sum(Range(age > 40), field="age")'
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```
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``` response
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{"results":[{"sum":191,"count":3}]}
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{"results":[{"value":191,"count":3}]}
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```
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Notice in this case that the count is only `3` because of the `age > 40` filter applied to the query.
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@ -499,42 +527,42 @@ To find the minimum age of all patients, run a `Min` query:
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``` request
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curl localhost:10101/index/patients/query \
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-X POST \
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-d 'Min(frame="measurements", field="age")'
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-d 'Min(field="age")'
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```
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``` response
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{"results":[{"min":19,"count":1}]}
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{"results":[{"value":19,"count":1}]}
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```
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The results you get from the `Min` query contain the `min` of all values as well as the `count` of columns with that value.
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The results you get from the `Min` query contain the minimum `value` of all values as well as the `count` of columns with that value.
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You can also provide a filter to the `Min()` function to find the minimum age of all patients over 40.
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``` request
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curl localhost:10101/index/patients/query \
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-X POST \
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-d 'Min(Range(frame="measurements", age > 40), frame="measurements", field="age")'
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-d 'Min(Range(age > 40), field="age")'
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```
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``` response
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{"results":[{"min":57,"count":1}]}
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{"results":[{"value":57,"count":1}]}
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```
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To find the maximum age of all patients, run a `Max` query:
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``` request
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curl localhost:10101/index/patients/query \
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-X POST \
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-d 'Max(frame="measurements", field="age")'
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-d 'Max(field="age")'
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```
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``` response
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{"results":[{"max":71,"count":1}]}
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{"results":[{"value":71,"count":1}]}
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```
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The results you get from the `Max` query contain the `max` of all values as well as the `count` of columns with that value.
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The results you get from the `Max` query contain the maximum `value` of all values as well as the `count` of columns with that value.
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You can also provide a filter to the `Max()` function to find the maximum age of all patients under 40.
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``` request
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curl localhost:10101/index/patients/query \
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-X POST \
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-d 'Max(Range(frame="measurements", age < 40), frame="measurements", field="age")'
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-d 'Max(Range(age < 40), field="age")'
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```
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``` response
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{"results":[{"max":34,"count":1}]}
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{"results":[{"value":34,"count":1}]}
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```
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### Storing Row and Column Attributes
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@ -549,28 +577,28 @@ curl localhost:10101/index/books \
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-X POST
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```
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``` response
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{}
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{"success":true}
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```
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Next, create a frame in the `books` index called `members` which will represent library members who have read books.
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Next, create a field in the `books` index called `members` which will represent library members who have read books.
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``` request
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curl localhost:10101/index/books/frame/members \
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curl localhost:10101/index/books/field/members \
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-X POST \
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-d '{}'
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```
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``` response
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{}
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{"success":true}
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```
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Now, let's add some books to our index.
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``` request
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curl localhost:10101/index/books/query \
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-X POST \
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-d 'SetColumnAttrs(col=1, name="To Kill a Mockingbird", year=1960)
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SetColumnAttrs(col=2, name="No Name in the Street", year=1972)
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SetColumnAttrs(col=3, name="The Tipping Point", year=2000)
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SetColumnAttrs(col=4, name="Out Stealing Horses", year=2003)
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SetColumnAttrs(col=5, name="The Forever War", year=2008)'
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-d 'SetColumnAttrs(1, name="To Kill a Mockingbird", year=1960)
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SetColumnAttrs(2, name="No Name in the Street", year=1972)
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SetColumnAttrs(3, name="The Tipping Point", year=2000)
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SetColumnAttrs(4, name="Out Stealing Horses", year=2003)
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SetColumnAttrs(5, name="The Forever War", year=2008)'
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```
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``` response
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{"results":[null,null,null,null,null]}
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@ -580,11 +608,11 @@ And add some members.
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``` request
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curl localhost:10101/index/books/query \
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-X POST \
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-d 'SetRowAttrs(frame="members", row=10001, fullName="John Smith")
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SetRowAttrs(frame="members", row=10002, fullName="Sue Perkins")
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SetRowAttrs(frame="members", row=10003, fullName="Jennifer Hawks")
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SetRowAttrs(frame="members", row=10004, fullName="Pedro Vazquez")
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SetRowAttrs(frame="members", row=10005, fullName="Pat Washington")'
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-d 'SetRowAttrs(members, 10001, fullName="John Smith")
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SetRowAttrs(members, 10002, fullName="Sue Perkins")
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SetRowAttrs(members, 10003, fullName="Jennifer Hawks")
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SetRowAttrs(members, 10004, fullName="Pedro Vazquez")
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SetRowAttrs(members, 10005, fullName="Pat Washington")'
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```
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``` response
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{"results":[null,null,null,null,null]}
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@ -594,29 +622,29 @@ At this point we can query one of the `member` records by querying that row.
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``` request
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curl localhost:10101/index/books/query \
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-X POST \
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-d 'Bitmap(frame="members", row=10002)'
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-d 'Row(members=10002)'
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```
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``` response
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{"results":[{"attrs":{"fullName":"Sue Perkins"},"bits":[]}]}
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{"results":[{"attrs":{"fullName":"Sue Perkins"},"columns":[]}]}
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```
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Now let's add some data to the matrix such that each pair represents a member who has read that book.
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``` request
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curl localhost:10101/index/books/query \
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-X POST \
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-d 'SetBit(frame="members", row=10001, col=3)
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SetBit(frame="members", row=10001, col=5)
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SetBit(frame="members", row=10002, col=1)
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SetBit(frame="members", row=10002, col=2)
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SetBit(frame="members", row=10002, col=4)
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SetBit(frame="members", row=10003, col=3)
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SetBit(frame="members", row=10004, col=4)
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SetBit(frame="members", row=10004, col=5)
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SetBit(frame="members", row=10005, col=1)
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SetBit(frame="members", row=10005, col=2)
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SetBit(frame="members", row=10005, col=3)
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SetBit(frame="members", row=10005, col=4)
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SetBit(frame="members", row=10005, col=5)'
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-d 'Set(3, members=10001)
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Set(5, members=10001)
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Set(1, members=10002)
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Set(2, members=10002)
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Set(4, members=10002)
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Set(3, members=10003)
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Set(4, members=10004)
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Set(5, members=10004)
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Set(1, members=10005)
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Set(2, members=10005)
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Set(3, members=10005)
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Set(4, members=10005)
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Set(5, members=10005)'
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```
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``` response
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{"results":[true,true,true,true,true,true,true,true,true,true,true,true,true]}
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@ -626,22 +654,22 @@ Now pull the record for `Sue Perkins` again.
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``` request
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curl localhost:10101/index/books/query \
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-X POST \
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-d 'Bitmap(frame="members", row=10002)'
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-d 'Row(members=10002)'
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```
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``` response
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{"results":[{"attrs":{"fullName":"Sue Perkins"},"bits":[1,2,4]}]}
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{"results":[{"attrs":{"fullName":"Sue Perkins"},"columns":[1,2,4]}]}
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```
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Notice that the result set now contains a list of integers in the `bits` attribute. These integers match the column IDs of the books that Sue has read.
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Notice that the result set now contains a list of integers in the `columns` attribute. These integers match the column IDs of the books that Sue has read.
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In order to retrieve the attribute information that we stored for each book, we need to add a URL parameter `columnAttrs=true` to the query.
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``` request
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curl localhost:10101/index/books/query?columnAttrs=true \
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-X POST \
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-d 'Bitmap(frame="members", row=10002)'
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-d 'Row(members=10002)'
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```
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``` response
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{
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"results":[{"attrs":{"fullName":"Sue Perkins"},"bits":[1,2,4]}],
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"results":[{"attrs":{"fullName":"Sue Perkins"},"columns":[1,2,4]}],
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"columnAttrs":[
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{"id":1,"attrs":{"name":"To Kill a Mockingbird","year":1960}},
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{"id":2,"attrs":{"name":"No Name in the Street","year":1972}},
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@ -655,11 +683,11 @@ Finally, if we want to find out which books were read by both `Sue` and `Pedro`,
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``` request
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curl localhost:10101/index/books/query?columnAttrs=true \
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-X POST \
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-d 'Intersect(Bitmap(frame="members", row=10002), Bitmap(frame="members", row=10004))'
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-d 'Intersect(Row(members=10002), Row(members=10004))'
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```
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``` response
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{
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"results":[{"attrs":{},"bits":[4]}],
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"results":[{"attrs":{},"columns":[4]}],
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"columnAttrs":[
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{"id":4,"attrs":{"name":"Out Stealing Horses","year":2003}}
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]
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