Time Series
Fetch ready-to-chart time series data.
Use cases
Time Series visualization
Visualize time series data in your apps.
In-app sparklines
Create inline visualizations in your apps.
Features
All the common API features, plus:
Aggregate data by various time granularities.
Available granularities:
MINUTE: Aggregates values by minute intervalsFIVE_MINUTES: Aggregates values by 5-minute intervalsTEN_MINUTES: Aggregates values by 10-minute intervalsFIFTEEN_MINUTES: Aggregates values by 15-minute intervalsHOUR: Aggregates values by hourly intervalsDAY: Aggregates values by daily intervalsWEEK: Aggregates values by weekly intervalsMONTH: Aggregates values by monthly intervalsYEAR: Aggregates values by yearly intervals
Group results by specific columns.
query TimeSeriesWithGroupByExample {
timeSeries(input: {
...
groupBy: ["restaurant_name"]
...
}) {
labels
values
}
}
Automatically zero-fills missing data points to ensure consistent time series.
Calculates time series granules for the given time zone, allowing for accurate representation of data across different geographical locations.
query TimeSeriesWithGroupByExample {
timeSeries(input: {
...
timeZone: "America/Los_Angeles"
...
}) {
labels
values
}
}
Example
Example 1: Simple time series query
Get the total taco sales for the last 3 days, filtered by the restaurant name.
query TimeSeriesExample1 {
timeSeries(input: {
metric: {
sum: {
dataPool: {
name: "TacoSoft Demo Data"
},
measure: {
columnName: "taco_total_price"
}
}
},
granularity: DAY,
timeRange: {
relative: LAST_N_DAYS,
n: 3
},
filterSql: "restaurant_name = 'El Buen Sabor'"
}) {
labels
values
}
}
Usage
Arguments
The fields for querying a Metric in time series format.
A Metric’s time series query returns the values over a given time range aggregated by a given time granularity; day, month, or year, for example.
The Metric to Query. It can be a pre-created one or it can be inlined here.
The ID of a pre-configured Metric.
The name of a pre-configured Metric.
An ad hoc Sum Metric.
An ad hoc Average Metric.
An ad hoc Min Metric.
An ad hoc Max Metric.
An ad hoc Count Distinct Metric.
The time range for calculating the time series.
The fields required to specify the time range for a time series, counter, or leaderboard Metric query.
If no relative or absolute time ranges are provided, Propel defaults to an absolute time range beginning with the earliest record in the Metric’s Data Pool and ending with the latest record.
If both relative and absolute time ranges are provided, the relative time range will take precedence.
If a LAST_N relative time period is selected, an n ≥ 1 must be provided. If no n is provided or n < 1, a BAD_REQUEST error will be returned.
The timestamp field to use when querying. Defaults to the timestamp configured on the Data Pool or Metric, if any. Set this to filter on an alternative timestamp field.
The relative time period.
The Relative time ranges are based on the current date and time.
THIS - The current unit of time. For example, if today is June 8, 2022, and
THIS_MONTH is selected, then data for June 2022 would be returned.
PREVIOUS - The previous unit of time. For example, if today is June 8, 2022, and
PREVIOUS_MONTH is selected, then data for May 2022 would be returned. It excludes
the current unit of time.
NEXT - The next unit of time. For example, if today is June 8, 2022, and
NEXT_MONTH is selected, then data for July 2022 would be returned. It excludes
the current unit of time.
LAST_N - The last n units of time, including the current one. For example, if today
is June 8, 2022 and LAST_N_YEARS with n = 3 is selected, then data for 2020, 2021, and
2022 will be returned. It will include the current time period.
THIS_HOUR: Starts at the zeroth minute of the current hour and continues for 60 minutes.TODAY: Starts at 12:00:00 AM of the current day and continues for 24 hours.THIS_WEEK: Starts on Monday, 12:00:00 AM of the current week and continues for seven days.THIS_MONTH: Starts at 12:00:00 AM on the first day of the current month and continues for the duration of the month.THIS_QUARTER: Starts at 12:00:00 AM on the first day of the current calendar quarter and continues for the duration of the quarter.THIS_YEAR: Starts on January 1st, 12:00:00 AM of the current year and continues for the duration of the year.PREVIOUS_HOUR: Starts at the zeroth minute of the previous hour and continues for 60 minutes.YESTERDAY: Starts at 12:00:00 AM on the day before the today and continues for 24 hours.PREVIOUS_WEEK: Starts on Monday, 12:00:00 AM, a week before the current week, and continues for seven days.PREVIOUS_MONTH: Starts at 12:00:00 AM on the first day of the month before the current month and continues for the duration of the month.PREVIOUS_QUARTER: Starts at 12:00:00 AM on the first day of the calendar quarter before the current quarter and continues for the duration of the quarter.PREVIOUS_YEAR: Starts on January 1st, 12:00:00 AM, the year before the current year, and continues for the duration of the year.NEXT_HOUR: Starts at the zeroth minute of the next hour and continues for 60 minutes.TOMORROW: ” Starts at 12:00:00 AM, the day after the current day, and continues for 24 hours.NEXT_WEEK: Starts on Monday, 12:00:00 AM, the week after the current week, and continues for the duration of the week.NEXT_MONTH: Starts at 12:00:00 AM on the first day of the next month and continues for the duration of the month.NEXT_QUARTER: Starts at 12:00:00 AM on the first day of the next calendar quarter and continues for the duration of the quarter.NEXT_YEAR: Starts on January 1st, 12:00:00 AM of the next year and continues for the duration of the year.LAST_N_MINUTES: Starts at the zeroth secondn- 1 minute(s) before the current minute and continues through the current minute. It includes this minute.LAST_N_HOURS: Starts at the zeroth minute of then- 1 hour(s) before the current hour, and continues through the current hour. It includes this hour.LAST_N_DAYS: Starts at 12:00:00 AM,n- 1 day(s) before the current day, and continues through the current day. It includes today.LAST_N_WEEKS: Starts on Monday, 12:00:00 AM,n- 1 week(s) before the current week, and continues through the current week. It includes this week.LAST_N_MONTHS: Starts at 12:00:00 AM on the first day of the month,n- 1 month(s) before the current month, and continues through the current month. It includes this month.LAST_N_QUARTERS: Starts at 12:00:00 AM on the first day of the calendar quartern- 1 quarter(s) before the current quarter and continues through the current quarter. It includes this quarter.LAST_N_YEARS: Starts on January 1st, 12:00:00 AM of the yearn- 1 year(s) before the current year and continues through the current year. It includes this year.LAST_15_MINUTESLAST_30_MINUTESLAST_HOURLAST_4_HOURSLAST_12_HOURSLAST_24_HOURSLAST_7_DAYSLAST_30_DAYSLAST_90_DAYSLAST_3_MONTHSLAST_6_MONTHSLAST_YEARLAST_2_YEARSLAST_5_YEARS
The number of time units for the LAST_N relative periods.
The optional start timestamp (inclusive). Defaults to the timestamp of the earliest record in the Data Pool.
The optional end timestamp (exclusive). Defaults to the timestamp of the latest record in the Data Pool.
The time zone to use. Dates and times are always returned in UTC, but setting the time zone influences relative time ranges and granularities.
You can set this to “America/Los_Angeles”, “Europe/Berlin”, or any other value in the IANA time zone database. Defaults to “UTC”.
The time granularity (hour, day, month, etc.) to aggregate the Metric values by.
The available time series granularities. Granularities define the unit of time to aggregate the Metric data for a time series query.
For example, if the granularity is set to DAY, then the the time series query will return a label and a value for each day.
If there are no records for a given time series granularity, Propel will return the label and a value of “0” so that the time series can be properly visualized.
MINUTE: Aggregates values by minute intervals.FIVE_MINUTES: Aggregates values by 5-minute intervals.TEN_MINUTES: Aggregates values by 10-minute intervals.FIFTEEN_MINUTES: Aggregates values by 15-minute intervals.HOUR: Aggregates values by hourly intervals.DAY: Aggregates values by daily intervals.WEEK: Aggregates values by weekly intervals.MONTH: Aggregates values by monthly intervals.YEAR: Aggregates values by yearly intervals.
The Query Filters to apply before retrieving the time series data, in the form of SQL. If no Query Filters are provided, all data is included.
Columns to group by.
The ID of the Metric to query.
Required if metricName is not specified.
metricThe name of the Metric to query.
Required if metricId is not specified.
metricThe Query Filters to apply before retrieving the time series data. If no Query Filters are provided, all data is included.
deprecated: UsefilterSql insteadThe fields of a filter.
You can construct more complex filters using and and or. For example, to construct a filter equivalent to
(value > 0 AND value <= 100) OR status = "confirmed"
you could write
{
"column": "value",
"operator": "GREATER_THAN",
"value": "0",
"and": [{
"column": "value",
"operator": "LESS_THAN_OR_EQUAL_TO",
"value": "0"
}],
"or": [{
"column": "status",
"operator": "EQUALS",
"value": "confirmed"
}]
}
Note that and takes precedence over or.
The name of the column to filter on.
The operation to perform when comparing the column and filter values.
The available Filter operators.
EQUALS: Selects values that are equal to the specified value.NOT_EQUALS: Selects values that are not equal to the specified value.GREATER_THAN: Selects values that are greater than the specified value.GREATER_THAN_OR_EQUAL_TO: Selects values that are greater or equal to the specified value.LESS_THAN: Selects values that are less than the specified value.LESS_THAN_OR_EQUAL_TO: Selects values that are less or equal to the specified value.IS_NULL: Selects values that are null. This operator does not accept a value.IS_NOT_NULL: Selects values that are not null. This operator does not accept a value.LIKE: Selects values that match the specified pattern.NOT_LIKE: “Selects values that do not match the specified pattern.
The value to compare the column to.
Additional filters to AND with this one. AND takes precedence over OR.
Additional filters to OR with this one. AND takes precedence over OR.
Response
The time series response object. It contains an array of time series labels and an array of Metric values for the given time range and Query Filters.
The time series labels.
The time series values.
The time series values for each group in groupBy, if specified.
The time series response object for a group specified in groupBy. It contains an array of time series labels and an array of Metric values for a particular group.
The time series group’s columns.
The time series group’s labels.
The time series group’s values.
The Query statistics and metadata.
The Query Info object. It contains metadata and statistics about a Query performed.
The Query’s unique identifier.
The date and time in UTC when the Query was created.
The unique identifier of the actor that performed the Query.
The date and time in UTC when the Query was last modified.
The unique identifier of the actor that modified the Query.
The bytes processed by the Query.
The duration of the Query in milliseconds.
The number of records processed by the Query.
The bytes returned by the Query.
The number of records returned by the Query.
The Propeller used for this query.
A Propeller determines your Application’s query processing power. The larger the Propeller, the faster the queries and the higher the cost. Every Propel Application (and therefore every set of API credentials) has a Propeller that determines the speed and cost of queries.
P1_X_SMALL: Max records per second: 5,000,000 records per secondP1_SMALL: Max records per second: 25,000,000 records per secondP1_MEDIUM: Max records per second: 100,000,000 records per secondP1_LARGE: Max records per second: 250,000,000 records per secondP1_X_LARGE: Max records per second: 500,000,000 records per second
The Query status.
The Query status.
COMPLETED: The Query was completed succesfully.ERROR: The Query experienced an error.TIMED_OUT: The Query timed out.
The Query type.
The Query type.
METRIC: Indicates a Metric Query.STATS: Indicates a Dimension Stats Query.REPORT: Indicates a Report Query.RECORDS: Indicates a Record Table Query.RECORDS_BY_UNIQUE_ID: Indicates records queried by unique ID.SQL: Indicates a SQL Query.TOP_VALUES: Indicates a Top Values Query.
The Query subtype.
The Query subtype.
COUNTER: Indicates a Metric counter Query.TIME_SERIES: Indicates a Metric time series Query.LEADERBOARD: Indicates a Metric leaderboard Query.
The SQL the query executed.
Embeddable UI components
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