Related to "transformations"
aggregateWindow() function
The aggregateWindow() function applies an aggregate function to fixed windows of time.
bottom() function
The bottom() function sorts a table by columns and keeps only the bottom n records.
chandeMomentumOscillator() function
The chandeMomentumOscillator() function applies the technical momentum indicator developed by Tushar Chande.
columns() function
The columns() function lists the column labels of input tables. For each input table, it outputs a table with the same group key columns, plus a new column containing the labels of the input table’s columns.
count() function
The count() function outputs the number of non-null records in a column.
cov() function
The cov() function computes the covariance between two streams by first joining the streams, then performing the covariance operation.
covariance() function
The covariance() function computes the covariance between two columns.
cumulativeSum() function
The cumulativeSum() function computes a running sum for non-null records in the table.
derivative() function
The derivative() function computes the rate of change per unit of time between subsequent non-null records.
difference() function
The difference() function computes the difference between subsequent non-null records.
distinct() function
The distinct() function returns the unique values for a given column.
doubleEMA() function
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().
drop() function
The drop() function removes specified columns from a table.
duplicate() function
The duplicate() function duplicates a specified column in a table.
elapsed() function
The elapsed() function returns the time between subsequent records.
exponentialMovingAverage() function
The exponentialMovingAverage() function calculates the exponential moving average of values in the _value column grouped into n number of points, giving more weight to recent data.
fill() function
The fill() function replaces all null values in an input stream and replace them with a non-null value.
filter() function
The filter() function filters data based on conditions defined in a predicate function (fn).
first() function
The first() function selects the first non-null record from an input table.
group() function
The group() function groups records based on their values for specific columns.
highestAverage() function
The highestAverage() function calculates the average of each table in the input stream returns the top n records.
highestCurrent() function
The highestCurrent() function selects the last record of each table in the input stream and returns the top n records.
highestMax() function
The highestMax() function selects the maximum record from each table in the input stream and returns the top n records.
histogram() function
The histogram() function approximates the cumulative distribution of a dataset by counting data frequencies for a list of bins.
histogramQuantile() function
The histogramQuantile() function approximates a quantile given a histogram that approximates the cumulative distribution of the dataset.
holtWinters() function
The holtWinters() function applies the Holt-Winters forecasting method to input tables.
hourSelection() function
The hourSelection() function retains all rows with time values in a specified hour range. Hours are specified in military time.
increase() function
The increase() function calculates the cumulative sum of non-negative differences between subsequent values.
integral() function
The integral() function computes the area under the curve per unit of time of subsequent non-null records.
join() function
The join() function merges two input streams into a single output stream based on columns with equal values.
kaufmansAMA() function
The kaufmansAMA() function calculates the Kaufman’s Adaptive Moving Average (KAMA) using values in an input table.
kaufmansER() function
The kaufmansER() function calculates the Kaufman’s Efficiency Ratio (KER) using values in an input table.
keep() function
The keep() function returns a table containing only the specified columns.
keys() function
The keys() function outputs the group key of input tables. For each input table, it outputs a table with the same group key columns, plus a _value column containing the labels of the input table’s group key.
keyValues() function
The keyValues() function returns a table with the input table’s group key plus two columns, _key and _value, that correspond to unique column + value pairs from the input table.
last() function
The last() function selects the last non-null record from an input table.
limit() function
The limit() function limits each output table to the first n records.
lowestAverage() function
The lowestAverage() function calculates the average of each table in the input stream returns the lowest n records.
lowestCurrent() function
The lowestCurrent() function selects the last record of each table in the input stream and returns the lowest n records.
lowestMin() function
The lowestMin() function selects the minimum record from each table in the input stream and returns the lowest n records.
map() function
The map() function applies a function to each record in the input tables.
max() function
The max() function selects record with the highest _value from the input table.
mean() function
The mean() function computes the mean or average of non-null records in the input table.
median() function
The median() function returns the median _value of an input table or all non-null records in the input table with values that fall within the 0.5 quantile or 50th percentile.
min() function
The min() function selects record with the lowest _value from the input table.
mode() function
The mode() function computes the mode or value that occurs most often in a specified column in the input table.
movingAverage() function
The movingAverage() function calculates the mean of values grouped into n number of points.
pearsonr() function
The pearsonr() function computes the Pearson R correlation coefficient between two streams by first joining the streams, then performing the covariance operation normalized to compute R.
pivot() function
The pivot() function collects values stored vertically (column-wise) in a table and aligns them horizontally (row-wise) into logical sets.
quantile() function
The quantile() function outputs non-null records with values that fall within the specified quantile or the non-null record with the value that represents the specified quantile.
range() function
The range() function filters records based on time bounds.
reduce() function
The reduce() function aggregates records in each table according to the reducer, fn, providing a way to create custom table aggregations.
relativeStrengthIndex() function
The relativeStrengthIndex() function measures the relative speed and change of values in an input table.
rename() function
The rename() function renames specified columns in a table.
sample() function
The sample() function selects a subset of the records from the input table.
set() function
The set() function assigns a static value to each record in the input table.
skew() function
The skew() function outputs the skew of non-null records as a float.
sort() function
The sort() function orders the records within each table.
spread() function
The spread() function outputs the difference between the minimum and maximum values in a specified column.
stateCount() function
The stateCount() function computes the number of consecutive records in a given state.
stateDuration() function
The stateDuration() function computes the duration of a given state.
stddev() function
The stddev() function computes the standard deviation of non-null records in a specified column.
sum() function
The sum() function computes the sum of non-null records in a specified column.
tail() function
The tail() function limits each output table to the last n records.
timedMovingAverage() function
The timedMovingAverage() function calculates the mean of values in a defined time range at a specified frequency.
timeShift() function
The timeShift() function adds a fixed duration to time columns.
timeWeightedAvg() function
The timeWeightedAvg() function outputs the timeWeightedAvg of non-null records as a float.
toBool() function
The toBool() function converts all values in the _value column to booleans.
toDuration() function
The toDuration() function converts all values in the _value column to durations.
toFloat() function
The toFloat() function converts all values in the _value column to floats.
toInt() function
The toInt() function converts all values in the _value column to integers.
top() function
The top() function sorts a table by columns and keeps only the top n records.
toString() function
The toString() function converts all values in the _value column to strings.
toTime() function
The toTime() function converts all values in the _value column to times.
toUInt() function
The toUInt() function converts all values in the _value column to UIntegers.
tripleEMA() function
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().
tripleExponentialDerivative() function
The tripleExponentialDerivative() function calculates a triple exponential derivative (TRIX) of input tables using n points.
truncateTimeColumn() function
The truncateTimeColumn() function truncates all input table _time values to a specified unit.
union() function
The union() function concatenates two or more input streams into a single output stream.
unique() function
The unique() function returns all records containing unique values in a specified column.
window() function
The window() function groups records based on a time value.
monitor.check() function
The monitor.check() function checks input data and assigns a level (ok, info, warn, or crit) to each row based on predicate functions.
monitor.deadman() function
The monitor.deadman() function detects when a group stops reporting data.
monitor.stateChanges() function
The monitor.stateChanges() function detects state changes in a stream of tables and outputs records that change from fromLevel to toLevel.
monitor.stateChangesOnly() function
The monitor.stateChangesOnly() function takes a stream of tables that contains a _level column and returns a stream of tables where each record represents a state change.
aggregate.rate() function
The aggregate.rate() function calculates the rate of change per windows of time.
schema.fieldsAsCols() function
The schema.fieldsAsCols() function pivots a table to automatically align fields within each input table that have the same timestamp.
testing.assertEmpty() function
The testing.assertEmpty() function tests if an input stream is empty.
testing.assertEquals() function
The testing.assertEquals() function tests whether two streams have identical data.
testing.benchmark() function
The testing.benchmark() function executes a test case without comparing test output with the expected test output. This lets you accurately benchmark a test case without the added overhead of comparing test output that occurs in testing.run().
testing.diff() function
The testing.diff() function produces a diff between two streams.
testing.inspect() function
The testing.inspect() function returns information about a test case.
testing.load() function
The testing.load() function loads tests data from a stream of tables.
v1.fieldsAsCols() function
The v1.fieldsAsCols() function pivots a table to automatically align fields within each input table that have the same timestamp.
experimental.alignTime() function
The experimental.alignTime() function aligns input tables to a common start time.
experimental.count() function
The experimental.count() function outputs the number of records in each input table and returns the count in the _value column.
experimental.distinct() function
The experimental.distinct() function returns unique values from the _value column.
experimental.fill() function
The experimental.fill() function replaces all null values in the _value column with a non-null value.
experimental.first() function
The experimental.first() function returns the first record with a non-null value in the _value column.
experimental.group() function
The experimental.group() function introduces an extend mode to the existing group() function.
experimental.histogram() function
The experimental.histogram() function approximates the cumulative distribution of a dataset by counting data frequencies for a list of bins.
experimental.histogramQuantile() function
The experimental.histogramQuantile() function approximates a quantile given a histogram with the cumulative distribution of the dataset.
experimental.integral() function
The integral() function computes the area under the curve per unit of time of subsequent non-null records. Input tables must have _time and _value columns.
experimental.join() function
The experimental.join() function joins two streams of tables on the group key with the addition of the _time column.
experimental.kaufmansAMA() function
The experimental.kaufmansAMA() function calculates the Kaufman’s Adaptive Moving Average (KAMA) of input tables using the _value column in each table.
experimental.last() function
The experimental.last() function returns the last record with a non-null value in the _value column.
experimental.max() function
The experimental.max() function returns the record with the highest value in the _value column for each input table.
experimental.mean() function
The experimental.mean() function computes the mean or average of non-null values in the _value column of each input table.
experimental.min() function
The experimental.min() function returns the record with the lowest value in the _value column for each input table.
experimental.mode() function
The experimental.mode() function computes the mode or value that occurs most often in the _value column in each input table.
experimental.preview() function
experimental.preview() limits the number of rows and tables in the stream.
experimental.quantile() function
The experimental.quantile() function outputs non-null records with values in the _value column that fall within the specified quantile or the non-null record with the value in the _value column that represents the specified quantile.
experimental.set() function
The experimental.set() function sets multiple static column values on all records.
experimental.skew() function
The experimental.skew() function outputs the skew of non-null values in the _value column for each input table.
experimental.spread() function
The experimental.spread() function outputs the difference between the minimum and maximum values in the _value column for each input table.
experimental.stddev() function
The experimental.stddev() function computes the standard deviation of non-null values in the _value column for each input table.
experimental.sum() function
The experimental.sum() function computes the sum of non-null records in a specified column.
experimental.unique() function
The experimental.unique() function returns all records containing unique values in the _value column.
experimental.window() function
The experimental.window() function groups records based on a time value. Input tables must have _start, _stop, and _time columns.
tickscript.alert() function
The tickscript.alert() function identifies events of varying severity levels and writes them to the statuses measurement in the InfluxDB _monitoring system bucket.
tickscript.compute() function
The tickscript.compute() function is an alias for tickscript.select() that changes a column’s name and optionally applies an aggregate or selector function to values in the column.
tickscript.deadman() function
The tickscript.deadman() function detects low data throughput and writes a point with a critical status to the InfluxDB _monitoring system bucket.
tickscript.groupBy() function
The tickscript.groupBy() function groups results by the _measurement column and other specified columns.
tickscript.join() function
The tickscript.join() function merges two input streams into a single output stream based on specified columns with equal values and appends a new measurement name.
tickscript.select() function
The tickscript.select() function changes a column’s name and optionally applies an aggregate or selector function to values in the column.
tickscript.selectWindow() function
The tickscript.selectWindow() function changes a column’s name, windows rows by time, and applies an aggregate or selector function the specified column for each window of time.
geo.asTracks() function
The geo.asTracks() function groups rows into tracks (sequential, related data points).
geo.filterRows() function
The geo.filterRows() function filters data by a specified geographic region with the option of strict filtering.
geo.gridFilter() function
The geo.gridFilter() function filters data by a specified geographic region.
geo.groupByArea() function
The geo.groupByArea() function groups rows by geographic area.
geo.shapeData() function
The geo.shapeData() function renames existing latitude and longitude fields to lat and lon and adds an s2_cell_id tag. Use geo.shapeData() to ensure geo-temporal data meets the requirements of the Geo package.
geo.ST_LineString() function
The geo.ST_LineString() function converts a series of geographic points into linestring.
geo.strictFilter() function
The geo.strictFilter() function filters data by latitude and longitude.
geo.toRows() function
The geo.toRows() function pivots data into row-wise sets base on time.
oee.APQ() function
The oee.APQ() function computes availability, performance, and quality (APQ) and overall equipment effectiveness (OEE).
oee.computeAPQ() function
The oee.computeAPQ() function computes availability, performance, and quality (APQ) and overall equipment effectiveness (OEE) using two separate input streams—production events and parts events.
prometheus.histogramQuantile() function
The prometheus.histogramQuantile() function calculates quantiles on a set of values assuming the given histogram data is scraped or read from a Prometheus data source.
query.filterFields() function
The query.filterFields() function filters input data by field.
query.filterMeasurement() function
The query.filterMeasurement() function filters input data by measurement.
table.fill() function
The table.fill() function adds a single row to empty tables in a stream of tables. Columns in the group key are filled with the column value defined in the group key. Columns not in the group key are filled with a null value.