Merge pull request #387 from influxdata/flux-0.38

Flux 0.38

content/v2.0/reference/flux/functions/built-in/transformations/aggregates/aggregatewindow.md

@@ -10,7 +10,8 @@ menu:
 weight: 501
 ---
 
-The `aggregateWindow()` function applies an aggregate function to fixed windows of time.
+The `aggregateWindow()` function applies an aggregate or selector function
+(any function with a `column` parameter) to fixed windows of time.
 
 _**Function type:** Aggregate_  
 
@@ -25,7 +26,7 @@ aggregateWindow(
 )
 ```
 
-As data is windowed into separate tables and aggregated, the `_time` column is dropped from each group key.
+As data is windowed into separate tables and processed, the `_time` column is dropped from each group key.
 This function copies the timestamp from a remaining column into the `_time` column.
 View the [function definition](#function-definition).
 
@@ -42,7 +43,7 @@ The [aggregate function](/v2.0/reference/flux/functions/built-in/transformations
 _**Data type:** Function_
 
 {{% note %}}
-Only aggregate functions with a `column` parameter (singular) work with `aggregateWindow()`.
+Only aggregate and selector functions with a `column` parameter (singular) work with `aggregateWindow()`.
 {{% /note %}}
 
 ### column
@@ -84,10 +85,10 @@ from(bucket: "example-bucket")
     fn: mean
   )
 ```
-###### Specifying parameters of the aggregate function
+###### Specify parameters of the aggregate function
-To use `aggregateWindow()` aggregate functions that don't provide defaults for required parameters,
+To use functions that don't provide defaults for required parameters with `aggregateWindow()`,
-for the `fn` parameter, define an anonymous function with `columns` and `tables` parameters
+define an anonymous function with `column` and `tables` parameters that pipe-forward
-that pipe-forwards tables into the aggregate function with all required parameters defined:
+tables into the aggregate or selector function with all required parameters defined:
 
 ```js
 from(bucket: "example-bucket")

content/v2.0/reference/flux/functions/built-in/transformations/aggregates/difference.md

@@ -17,7 +17,11 @@ _**Function type:** Aggregate_
 _**Output data type:** Float_
 
 ```js
-difference(nonNegative: false, column: "_value")
+difference(
+  nonNegative: false,
+  column: "_value",
+  keepFirst: false
+)
 ```
 
 ## Parameters
@@ -34,6 +38,13 @@ Defaults to `"_value"`.
 
 _**Data type:** String_
 
+### keepFirst
+Indicates the first row should be kept.
+If `true`, the difference will be `null`.
+Defaults to `false`.
+
+_**Data type:** Boolean_
+
 ## Subtraction rules for numeric types
 - The difference between two non-null values is their algebraic difference;
   or `null`, if the result is negative and `nonNegative: true`;
@@ -90,6 +101,20 @@ from(bucket: "example-bucket")
 | 0004  | 6      | tv  |
 | 0005  | null   | tv  |
 
+
+#### With keepFirst set to true
+```js
+|> difference(nonNegative: false, keepfirst: true):
+```
+###### Output table
+| _time | _value | tag |
+|:-----:|:------:|:---:|
+| 0001  | null   | tv  |
+| 0002  | null   | tv  |
+| 0003  | -2     | tv  |
+| 0004  | 6      | tv  |
+| 0005  | null   | tv  |
+
 <hr style="margin-top:4rem"/>
 
 ##### Related InfluxQL functions and statements:

content/v2.0/reference/flux/functions/built-in/transformations/aggregates/doubleema.md

@@ -0,0 +1,63 @@
+---
+title: doubleEMA() function
+description: >
+  The `doubleEMA()` function calculates the exponential moving average of values
+  grouped into `n` number of points, giving more weight to recent data at double
+  the rate of `exponentialMovingAverage()`.
+menu:
+  v2_0_ref:
+    name: doubleEMA
+    parent: built-in-aggregates
+weight: 501
+related:
+  - /v2.0/reference/flux/functions/built-in/transformations/aggregates/movingaverage/
+  - /v2.0/reference/flux/functions/built-in/transformations/aggregates/tripleema/
+  - /v2.0/reference/flux/functions/built-in/transformations/aggregates/timedmovingaverage/
+  - /v2.0/reference/flux/functions/built-in/transformations/aggregates/exponentialmovingaverage/
+  - https://docs.influxdata.com/influxdb/v1.7/query_language/functions/#double-exponential-moving-average, InfluxQL DOUBLE_EXPONENTIAL_MOVING_AVERAGE()
+---
+
+The `doubleEMA()` function calculates the exponential moving average of values in
+the `_value` column grouped into `n` number of points, giving more weight to recent
+data at double the rate of [`exponentialMovingAverage()`](/v2.0/reference/flux/functions/built-in/transformations/aggregates/exponentialmovingaverage/).
+
+_**Function type:** Aggregate_  
+
+```js
+doubleEMA(n: 5)
+```
+
+##### Double exponential moving average rules
+- A double exponential moving average is defined as `doubleEMA = 2 * EMA_N - EMA of EMA_N`.
+    - `EMA` is an exponential moving average.
+    - `N = n` is the period used to calculate the EMA.
+- A true double exponential moving average requires at least `2 * n - 1` values.
+  If not enough values exist to calculate the double EMA, it returns a `NaN` value.
+- `doubleEMA()` inherits all [exponential moving average rules](/v2.0/reference/flux/functions/built-in/transformations/aggregates/exponentialmovingaverage/#exponential-moving-average-rules).
+
+## Parameters
+
+### n
+The number of points to average.
+
+_**Data type:** Integer_
+
+## Examples
+
+#### Calculate a five point double exponential moving average
+```js
+from(bucket: "example-bucket"):
+  |> range(start: -12h)
+  |> doubleEMA(n: 5)
+```
+
+## Function definition
+```js
+doubleEMA = (n, tables=<-) =>
+  tables
+    |> exponentialMovingAverage(n:n)
+    |> duplicate(column:"_value", as:"ema")
+    |> exponentialMovingAverage(n:n)
+    |> map(fn: (r) => ({r with _value: 2.0 * r.ema - r._value}))
+    |> drop(columns: ["ema"])
+```

content/v2.0/reference/flux/functions/built-in/transformations/aggregates/exponentialmovingaverage.md

@@ -1,8 +1,8 @@
 ---
 title: exponentialMovingAverage() function
 description: >
-  The `exponentialMovingAverage()` function calculates the exponential moving average
+  The `exponentialMovingAverage()` function calculates the exponential moving average of values
-  of values grouped into `n` number of points, giving more weight to recent data.
+  in the `_value` column grouped into `n` number of points, giving more weight to recent data.
 menu:
   v2_0_ref:
     name: exponentialMovingAverage
@@ -11,22 +11,21 @@ weight: 501
 related:
   - /v2.0/reference/flux/functions/built-in/transformations/aggregates/movingaverage/
   - /v2.0/reference/flux/functions/built-in/transformations/aggregates/timedmovingaverage/
+  - /v2.0/reference/flux/functions/built-in/transformations/aggregates/doubleema/
+  - /v2.0/reference/flux/functions/built-in/transformations/aggregates/tripleema/
   - https://docs.influxdata.com/influxdb/v1.7/query_language/functions/#exponential-moving-average, InfluxQL EXPONENTIAL_MOVING_AVERAGE()
 ---
 
-The `exponentialMovingAverage()` function calculates the exponential moving average
+The `exponentialMovingAverage()` function calculates the exponential moving average of values
-of values grouped into `n` number of points, giving more weight to recent data.
+in the `_value` column grouped into `n` number of points, giving more weight to recent data.
 
 _**Function type:** Aggregate_  
 
 ```js
-exponentialMovingAverage(
+exponentialMovingAverage(n: 5)
-  n: 5,
-  columns: ["_value"]
-)
 ```
 
-##### Exponential moving average rules:
+##### Exponential moving average rules
 - The first value of an exponential moving average over `n` values is the
   algebraic mean of `n` values.
 - Subsequent values are calculated as `y(t) = x(t) * k + y(t-1) * (1 - k)`, where:
@@ -43,11 +42,6 @@ The number of points to average.
 
 _**Data type:** Integer_
 
-### columns
-Columns to operate on. _Defaults to `["_value"]`_.
-
-_**Data type:** Array of Strings_
-
 ## Examples
 
 #### Calculate a five point exponential moving average
@@ -60,23 +54,20 @@ from(bucket: "example-bucket"):
 #### Table transformation with a two point exponential moving average
 
 ###### Input table:
-| _time | A    | B    | C    | tag |
+| _time | tag | _value |
-|:-----:|:----:|:----:|:----:|:---:|
+|:-----:|:---:|:------:|
-| 0001  | 2    | null | 2    | tv  |
+| 0001  | tv  | null   |
-| 0002  | null | 10   | 4    | tv  |
+| 0002  | tv  | 10     |
-| 0003  | 8    | 20   | 5    | tv  |
+| 0003  | tv  | 20     |
 
 ###### Query:
 ```js
 // ...
-  |> exponentialMovingAverage(
+  |> exponentialMovingAverage(n: 2)
-    n: 2,
-    columns: ["A", "B", "C"]
-  )
 ```
 
 ###### Output table:
-| _time | A    | B    | C    | tag |
+| _time | tag | _value |
-|:-----:|:----:|:----:|:----:|:---:|
+|:-----:|:---:|:------:|
-| 0002  | 2    | 10   | 3    | tv  |
+| 0002  | tv  | 10     |
-| 0003  | 6    | 16.67| 4.33 | tv  |
+| 0003  | tv  | 16.67  |

content/v2.0/reference/flux/functions/built-in/transformations/aggregates/holtwinters.md

@@ -0,0 +1,114 @@
+---
+title: holtWinters() function
+description: >
+  The `holtWinters()` function applies the Holt-Winters forecasting method to input tables.
+aliases:
+  - /v2.0/reference/flux/functions/transformations/aggregates/holtwinters
+menu:
+  v2_0_ref:
+    name: holtWinters
+    parent: built-in-aggregates
+weight: 501
+related:
+  - https://docs.influxdata.com/influxdb/latest/query_language/functions/#holt-winters, InfluxQL HOLT_WINTERS()
+---
+
+The `holtWinters()` function applies the Holt-Winters forecasting method to input tables.
+
+_**Function type:** Aggregate_  
+_**Output data type:** Float_
+
+```js
+holtWinters(
+  n: 10,
+  seasonality: 4,
+  interval: 30d,
+  withFit: false,
+  timeColumn: "_time",
+  column: "_value",
+)
+```
+
+The Holt-Winters method predicts [`n`](#n) seasonally-adjusted values for the
+specified [`column`](#column) at the specified [`interval`](#interval).
+For example, if `interval` is `6m` and `n` is `3`, results include three predicted
+values six minutes apart.
+
+#### Seasonality
+[`seasonality`](#seasonality) delimits the length of a seasonal pattern according to `interval`.
+If your `interval` is `2m` and `seasonality` is `4`, then the seasonal pattern occurs every
+eight minutes or every four data points.
+If data doesn't have a seasonal pattern, set `seasonality` to `0`.
+
+#### Space values evenly in time
+`holtWinters()` expects values evenly spaced in time.
+To ensure `holtWinters()` values are spaced evenly in time, the following rules apply:
+
+- Data is grouped into time-based "buckets" determined by the `interval`.
+- If a bucket includes many values, the first value is used.
+- If a bucket includes no values, a missing value (`null`) is added for that bucket.
+
+By default, `holtWinters()` uses the first value in each time bucket to run the Holt-Winters calculation.
+To specify other values to use in the calculation, use:
+
+- [`window()`](/v2.0/reference/flux/functions/built-in/transformations/window/)
+  with [selectors](/v2.0/reference/flux/functions/built-in/transformations/selectors/)
+  or [aggregates](/v2.0/reference/flux/functions/built-in/transformations/aggregates/)
+- [`aggregateWindow()`](/v2.0/reference/flux/functions/built-in/transformations/aggregates/aggregatewindow)
+
+#### Fitted model
+The `holtWinters()` function applies the [Nelder-Mead optimization](https://en.wikipedia.org/wiki/Nelder%E2%80%93Mead_method)
+to include "fitted" data points in results when [`withFit`](#withfit) is set to `true`.
+
+#### Null timestamps
+`holtWinters()` discards rows with `null` timestamps before running the Holt-Winters calculation.
+
+#### Null values
+`holtWinters()` treats `null` values as missing data points and includes them in the Holt-Winters calculation.
+
+## Parameters
+
+### n
+The number of values to predict.
+
+_**Data type: Integer**_
+
+### seasonality
+The number of points in a season.
+Defaults to `0`.
+
+_**Data type: Integer**_
+
+### interval
+The interval between two data points.
+
+_**Data type: Duration**_
+
+### withFit
+Return [fitted data](#fitted-model) in results.
+Defaults to `false`.
+
+_**Data type: Boolean**_
+
+### timeColumn
+The time column to use.
+Defaults to `"_time"`.
+
+_**Data type: String**_
+
+### column
+The column to operate on.
+Defaults to `"_value"`.
+
+_**Data type: String**_
+
+## Examples
+
+##### Use aggregateWindow to prepare data for holtWinters
+```js
+from(bucket: "example-bucket")
+    |> range(start: -7y)
+    |> filter(fn: (r) => r._field == "water_level")
+    |> aggregateWindow(every: 379m, fn: first).
+    |> holtWinters(n: 10, seasonality: 4, interval: 379m)
+```

content/v2.0/reference/flux/functions/built-in/transformations/aggregates/movingaverage.md

@@ -10,21 +10,21 @@ weight: 501
 related:
   - /v2.0/reference/flux/functions/built-in/transformations/aggregates/timedmovingaverage/
   - /v2.0/reference/flux/functions/built-in/transformations/aggregates/exponentialmovingaverage/
+  - /v2.0/reference/flux/functions/built-in/transformations/aggregates/doubleema/
+  - /v2.0/reference/flux/functions/built-in/transformations/aggregates/tripleema/
   - https://docs.influxdata.com/influxdb/latest/query_language/functions/#moving-average, InfluxQL MOVING_AVERAGE()
 ---
 
-The `movingAverage()` function calculates the mean of values grouped into `n` number of points.
+The `movingAverage()` function calculates the mean of values in the `_values` column
+grouped into `n` number of points.
 
 _**Function type:** Aggregate_  
 
 ```js
-movingAverage(
+movingAverage(n: 5)
-  n: 5,
-  columns: ["_value"]
-)
 ```
 
-##### Moving average rules:
+##### Moving average rules
 - The average over a period populated by `n` values is equal to their algebraic mean.
 - The average over a period populated by only `null` values is `null`.
 - Moving averages skip `null` values.
@@ -38,11 +38,6 @@ The number of points to average.
 
 _**Data type:** Integer_
 
-### columns
-Columns to operate on. _Defaults to `["_value"]`_.
-
-_**Data type:** Array of Strings_
-
 ## Examples
 
 #### Calculate a five point moving average
@@ -52,36 +47,23 @@ from(bucket: "example-bucket"):
   |> movingAverage(n: 5)
 ```
 
-#### Calculate a ten point moving average
-```js
-movingAverage = (every, period, column="_value", tables=<-) =>
-  tables
-    |> window(every: every, period: period)
-    |> mean(column: column)
-    |> duplicate(column: "_stop", as: "_time")
-    |> window(every: inf)
-```
-
 #### Table transformation with a two point moving average
 
 ###### Input table:
-| _time |   A  |   B  |   C  |   D  | tag |
+| _time | tag | _value |
-|:-----:|:----:|:----:|:----:|:----:|:---:|
+|:-----:|:---:|:------:|
-|  0001 | null |   1  |   2  | null |  tv |
+| 0001  | tv  | null   |
-|  0002 |   6  |   2  | null | null |  tv |
+| 0002  | tv  | 6      |
-|  0003 |   4  | null |   4  |   4  |  tv |
+| 0003  | tv  | 4      |
 
 ###### Query:
 ```js
 // ...
-  |> movingAverage(
+  |> movingAverage(n: 2 )
-    n: 2,
-    columns: ["A", "B", "C", "D"]
-  )
 ```
 
 ###### Output table:
-| _time |   A  |   B  |   C  |   D  | tag |
+| _time | tag | _value |
-|:-----:|:----:|:----:|:----:|:----:|:---:|
+|:-----:|:---:|:------:|
-|  0002 |   6  |  1.5 |   2  | null |  tv |
+| 0002  | tv  | 6      |
-|  0003 |   5  |   2  |   4  |   4  |  tv |
+| 0003  | tv  | 5      |

content/v2.0/reference/flux/functions/built-in/transformations/aggregates/relativestrengthindex.md

@@ -0,0 +1,103 @@
+---
+title: relativeStrengthIndex() function
+description: >
+  The `relativeStrengthIndex()` function measures the relative speed and change of
+  values in an input table.
+menu:
+  v2_0_ref:
+    name: relativeStrengthIndex
+    parent: built-in-aggregates
+weight: 501
+related:
+  - /v2.0/reference/flux/functions/built-in/transformations/aggregates/movingaverage/
+  - /v2.0/reference/flux/functions/built-in/transformations/aggregates/timedmovingaverage/
+  - /v2.0/reference/flux/functions/built-in/transformations/aggregates/exponentialmovingaverage/
+  - https://docs.influxdata.com/influxdb/v1.7/query_language/functions/#relative-strength-index, InfluxQL RELATIVE_STRENGTH_INDEX()
+---
+
+The `relativeStrengthIndex()` function measures the relative speed and change of
+values in an input table.
+
+_**Function type:** Aggregate_  
+
+```js
+relativeStrengthIndex(
+  n: 5,
+  columns: ["_value"]
+)
+```
+
+##### Relative strength index rules
+- The general equation for calculating a relative strength index (RSI) is
+  `RSI = 100 - (100 / (1 + (AVG GAIN / AVG LOSS)))`.
+- For the first value of the RSI, `AVG GAIN` and `AVG LOSS` are averages of the `n` period.
+- For subsequent calculations:
+  - `AVG GAIN` = `((PREVIOUS AVG GAIN) * (n - 1)) / n`
+  - `AVG LOSS` = `((PREVIOUS AVG LOSS) * (n - 1)) / n`
+- `relativeStrengthIndex()` ignores `null` values.
+
+## Parameters
+
+### n
+The number of values to use to calculate the RSI.
+
+_**Data type:** Integer_
+
+### columns
+Columns to operate on. _Defaults to `["_value"]`_.
+
+_**Data type:** Array of Strings_
+
+## Examples
+
+#### Calculate a five point relative strength index
+```js
+from(bucket: "example-bucket"):
+  |> range(start: -12h)
+  |> relativeStrengthIndex(n: 5)
+```
+
+#### Table transformation with a ten point RSI
+
+###### Input table:
+| _time | A    | B    | tag |
+|:-----:|:----:|:----:|:---:|
+| 0001  | 1    | 1    | tv  |
+| 0002  | 2    | 2    | tv  |
+| 0003  | 3    | 3    | tv  |
+| 0004  | 4    | 4    | tv  |
+| 0005  | 5    | 5    | tv  |
+| 0006  | 6    | 6    | tv  |
+| 0007  | 7    | 7    | tv  |
+| 0008  | 8    | 8    | tv  |
+| 0009  | 9    | 9    | tv  |
+| 0010  | 10   | 10   | tv  |
+| 0011  | 11   | 11   | tv  |
+| 0012  | 12   | 12   | tv  |
+| 0013  | 13   | 13   | tv  |
+| 0014  | 14   | 14   | tv  |
+| 0015  | 15   | 15   | tv  |
+| 0016  | 16   | 16   | tv  |
+| 0017  | 17   | null | tv  |
+| 0018  | 18   | 17   | tv  |
+
+###### Query:
+```js
+// ...
+  |> relativeStrengthIndex(
+    n: 10,
+    columns: ["A", "B"]
+  )
+```
+
+###### Output table:
+| _time |   A  |   B  | tag |
+|:-----:|:----:|:----:|:---:|
+|  0011 | 100  | 100  |  tv |
+|  0012 | 100  | 100  |  tv |
+|  0013 | 100  | 100  |  tv |
+|  0014 | 100  | 100  |  tv |
+|  0015 | 100  | 100  |  tv |
+|  0016 |  90  |  90  |  tv |
+|  0017 |  81  |  90  |  tv |
+|  0018 | 72.9 |  81  |  tv |

content/v2.0/reference/flux/functions/built-in/transformations/aggregates/timedmovingaverage.md

@@ -11,6 +11,8 @@ weight: 501
 related:
   - /v2.0/reference/flux/functions/built-in/transformations/aggregates/movingaverage/
   - /v2.0/reference/flux/functions/built-in/transformations/aggregates/exponentialmovingaverage/
+  - /v2.0/reference/flux/functions/built-in/transformations/aggregates/doubleema/
+  - /v2.0/reference/flux/functions/built-in/transformations/aggregates/tripleema/
   - https://docs.influxdata.com/influxdb/latest/query_language/functions/#moving-average, InfluxQL MOVING_AVERAGE()
 ---
 

content/v2.0/reference/flux/functions/built-in/transformations/aggregates/tripleema.md

@@ -0,0 +1,68 @@
+---
+title: tripleEMA() function
+description: >
+  The `tripleEMA()` function calculates the exponential moving average of values
+  grouped into `n` number of points, giving more weight to recent data with less lag
+  than `exponentialMovingAverage()` and `doubleEMA()`.
+menu:
+  v2_0_ref:
+    name: tripleEMA
+    parent: built-in-aggregates
+weight: 501
+related:
+  - /v2.0/reference/flux/functions/built-in/transformations/aggregates/movingaverage/
+  - /v2.0/reference/flux/functions/built-in/transformations/aggregates/doubleema/
+  - /v2.0/reference/flux/functions/built-in/transformations/aggregates/timedmovingaverage/
+  - /v2.0/reference/flux/functions/built-in/transformations/aggregates/exponentialmovingaverage/
+    - https://docs.influxdata.com/influxdb/v1.7/query_language/functions/#triple-exponential-moving-average, InfluxQL TRIPLE_EXPONENTIAL_MOVING_AVERAGE()
+---
+
+The `tripleEMA()` function calculates the exponential moving average of values in
+the `_value` column grouped into `n` number of points, giving more weight to recent
+data with less lag than
+[`exponentialMovingAverage()`](/v2.0/reference/flux/functions/built-in/transformations/aggregates/exponentialmovingaverage/)
+and [`doubleEMA()`](/v2.0/reference/flux/functions/built-in/transformations/aggregates/doubleema/).
+
+_**Function type:** Aggregate_  
+
+```js
+tripleEMA(n: 5)
+```
+
+##### Triple exponential moving average rules
+- A triple exponential moving average is defined as `tripleEMA = (3 * EMA_1) - (3 * EMA_2) + EMA_3`.
+  - `EMA_1` is the exponential moving average of the original data.
+  - `EMA_2` is the exponential moving average of `EMA_1`.
+  - `EMA_3` is the exponential moving average of `EMA_2`.
+- A true triple exponential moving average requires at least requires at least `3 * n - 2` values.
+  If not enough values exist to calculate the triple EMA, it returns a `NaN` value.
+- `tripleEMA()` inherits all [exponential moving average rules](/v2.0/reference/flux/functions/built-in/transformations/aggregates/exponentialmovingaverage/#exponential-moving-average-rules).
+
+## Parameters
+
+### n
+The number of points to average.
+
+_**Data type:** Integer_
+
+## Examples
+
+#### Calculate a five point triple exponential moving average
+```js
+from(bucket: "example-bucket"):
+  |> range(start: -12h)
+  |> tripleEMA(n: 5)
+```
+
+## Function definition
+```js
+tripleEMA = (n, tables=<-) =>
+	tables
+		|> exponentialMovingAverage(n:n)
+		|> duplicate(column:"_value", as:"ema1")
+    |> exponentialMovingAverage(n:n)
+		|> duplicate(column:"_value", as:"ema2")
+		|> exponentialMovingAverage(n:n)
+		|> map(fn: (r) => ({r with _value: 3.0 * r.ema1 - 3.0 * r.ema2 + r._value}))
+		|> drop(columns: ["ema1", "ema2"])
+```

content/v2.0/reference/flux/functions/date/microsecond.md

@@ -0,0 +1,31 @@
+---
+title: date.microsecond() function
+description: >
+  The `date.microsecond()` function returns the microsecond of a specified time.
+  Results range from `[0-999999]`.
+menu:
+  v2_0_ref:
+    name: date.microsecond
+    parent: Date
+weight: 301
+---
+
+The `date.microsecond()` function returns the microsecond of a specified time.
+Results range from `[0-999999]`.
+
+_**Function type:** Transformation_  
+
+```js
+import "date"
+
+date.microsecond(t: 2019-07-17T12:05:21.012934584Z)
+
+// Returns 12934
+```
+
+## Parameters
+
+### t
+The time to operate on.
+
+_**Data type:** Time_

content/v2.0/reference/flux/functions/date/millisecond.md

@@ -0,0 +1,31 @@
+---
+title: date.millisecond() function
+description: >
+  The `date.millisecond()` function returns the millisecond of a specified time.
+  Results range from `[0-999999]`.
+menu:
+  v2_0_ref:
+    name: date.millisecond
+    parent: Date
+weight: 301
+---
+
+The `date.millisecond()` function returns the millisecond of a specified time.
+Results range from `[0-999]`.
+
+_**Function type:** Transformation_  
+
+```js
+import "date"
+
+date.millisecond(t: 2019-07-17T12:05:21.012934584Z)
+
+// Returns 12
+```
+
+## Parameters
+
+### t
+The time to operate on.
+
+_**Data type:** Time_

content/v2.0/reference/flux/functions/date/nanosecond.md

@@ -0,0 +1,31 @@
+---
+title: date.nanosecond() function
+description: >
+  The `date.nanosecond()` function returns the nanosecond of a specified time.
+  Results range from `[0-999999999]`.
+menu:
+  v2_0_ref:
+    name: date.nanosecond
+    parent: Date
+weight: 301
+---
+
+The `date.nanosecond()` function returns the nanosecond of a specified time.
+Results range from `[0-999999999]`.
+
+_**Function type:** Transformation_  
+
+```js
+import "date"
+
+date.nanosecond(t: 2019-07-17T12:05:21.012934584Z)
+
+// Returns 12934584
+```
+
+## Parameters
+
+### t
+The time to operate on.
+
+_**Data type:** Time_

content/v2.0/reference/flux/functions/date/quarter.md

@@ -0,0 +1,31 @@
+---
+title: date.quarter() function
+description: >
+  The `date.quarter()` function returns the quarter of the year for a specified time.
+  Results range from `[1-4]`.
+menu:
+  v2_0_ref:
+    name: date.quarter
+    parent: Date
+weight: 301
+---
+
+The `date.quarter()` function returns the quarter of the year for a specified time.
+Results range from `[1-4]`.
+
+_**Function type:** Transformation_  
+
+```js
+import "date"
+
+date.quarter(t: 2019-07-17T12:05:21.012Z)
+
+// Returns 3
+```
+
+## Parameters
+
+### t
+The time to operate on.
+
+_**Data type:** Time_

content/v2.0/reference/flux/functions/date/truncate.md

@@ -0,0 +1,57 @@
+---
+title: date.truncate() function
+description: >
+  The `date.truncate()` function truncates a time to a specified unit.
+menu:
+  v2_0_ref:
+    name: date.truncate
+    parent: Date
+weight: 301
+---
+
+The `date.truncate()` function truncates a time to a specified unit.
+
+_**Function type:** Transformation_  
+
+```js
+import "date"
+
+date.truncate(
+  t: 2019-07-17T12:05:21.012Z
+  unit: 1s
+)
+
+// Returns 2019-07-17T12:05:21.000000000Z
+```
+
+## Parameters
+
+### t
+The time to operate on.
+
+_**Data type:** Time_
+
+### unit
+The unit time to truncate to.
+
+_**Data type:** Duration_
+
+{{% note %}}
+Only use `1` and the unit of time to specify the `unit`.
+For example: `1s`, `1m`, `1h`.
+{{% /note %}}
+
+## Examples
+```js
+import "date"
+
+date.truncate(t: "2019-06-03T13:59:01.000000000Z", unit: 1s)
+// Returns  2019-06-03T13:59:01.000000000Z
+
+date.truncate(t: "2019-06-03T13:59:01.000000000Z", unit: 1m)
+// Returns  2019-06-03T13:59:00.000000000Z
+
+date.truncate(t: "2019-06-03T13:59:01.000000000Z", unit: 1h)
+// Returns  2019-06-03T13:00:00.000000000Z
+
+```

content/v2.0/reference/flux/functions/date/week.md

@@ -0,0 +1,31 @@
+---
+title: date.week() function
+description: >
+  The `date.week()` function returns the ISO week of the year for a specified time.
+  Results range from `[1-53]`.
+menu:
+  v2_0_ref:
+    name: date.week
+    parent: Date
+weight: 301
+---
+
+The `date.week()` function returns the ISO week of the year for a specified time.
+Results range from `[1-53]`.
+
+_**Function type:** Transformation_  
+
+```js
+import "date"
+
+date.week(t: 2019-07-17T12:05:21.012Z)
+
+// Returns 29
+```
+
+## Parameters
+
+### t
+The time to operate on.
+
+_**Data type:** Time_

content/v2.0/reference/flux/functions/date/year.md

@@ -0,0 +1,30 @@
+---
+title: date.year() function
+description: >
+  The `date.year()` function returns the year of a specified time.
+menu:
+  v2_0_ref:
+    name: date.year
+    parent: Date
+weight: 301
+draft: true
+---
+
+The `date.year()` function returns the year of a specified time.
+
+_**Function type:** Transformation_  
+
+```js
+import "date"
+
+date.year(t: 2019-07-17T12:05:21.012Z)
+
+// Returns 2019
+```
+
+## Parameters
+
+### t
+The time to operate on.
+
+_**Data type:** Time_

content/v2.0/reference/flux/functions/runtime/_index.md

@@ -0,0 +1,22 @@
+---
+title: Flux runtime package
+list_title: Runtime package
+description: >
+  The Flux runtime package includes functions that provide information about the
+  current Flux runtime. Import the `runtime` package.
+menu:
+  v2_0_ref:
+    name: Runtime
+    parent: Flux packages and functions
+weight: 202
+v2.0/tags: [runtime, functions, package]
+---
+
+The Flux runtime package includes functions that provide information about the
+current Flux runtime. Import the `runtime` package:
+
+```js
+import "runtime"
+```
+
+{{< children type="functions" show="pages" >}}

content/v2.0/reference/flux/functions/runtime/version.md

@@ -0,0 +1,20 @@
+---
+title: runtime.version() function
+description: The `runtime.version()` function returns the current Flux version.
+menu:
+  v2_0_ref:
+    name: runtime.version
+    parent: Runtime
+weight: 401
+---
+
+The `runtime.version()` function returns the current Flux version.
+
+_**Function type:** Miscellaneous_  
+_**Output data type:** String_
+
+```js
+import "runtime"
+
+runtime.version()
+```

content/v2.0/reference/release-notes/flux.md

@@ -11,13 +11,37 @@ aliases:
 ---
 
 {{% note %}}
-_The latest release of InfluxDB v2.0 alpha includes **Flux v0.37.2**.
+_The latest release of InfluxDB v2.0 alpha includes **Flux v0.38.0**.
 Though newer versions of Flux may be available, they will not be included with
 InfluxDB until the next InfluxDB v2.0 release._
 {{% /note %}}
 
 ---
 
+## v0.38.0 [2019-08-06]
+
+### Features
+- Update selectors to operate on time columns.
+- Add `relativeStrengthIndex()` transformation.
+- Add double and triple exponential average transformations (`doubleEMA()` and `tripleEMA()`).
+- Add `holtWinters()` transformation.
+- Add `keepFirst` parameter to `difference()`.
+- DatePart equivalent functions.
+- Add runtime package.
+- Add and subtract duration literal arithmetic.
+- Allow `keep()` to run regardless of nonexistent columns.
+  If all columns given are nonexistent, `keep()` returns an empty table.
+- Scanner returns positioning.
+
+### Bug fixes
+- Function resolver now keeps track of local assignments that may be evaluated at runtime.
+- Fixed InfluxDB test errors.
+- Add range to tests to pass in InfluxDB.
+- Allow converting a duration to a duration.
+- Catch integer overflow and underflow for literals.
+
+---
+
 ## v0.37.2 [2019-07-24]
 
 -  _General cleanup of internal code._