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Update link (#4636)
* chore: update glossary internal links. * chore: update link * chore: inline links * chore: inline links
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about/whitepaper.md

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Want to read this whitepaper from the comfort of your own computer?
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<center>
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<Tag type="download">[Tiger Data architecture for real-time analytics (PDF)](https://assets.timescale.com/docs/downloads/tigerdata-whitepaper.pdf)</Tag>
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Download the PDF: <Tag type="download">[Tiger Data architecture for real-time analytics][whitepaper_pdf]</Tag>
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</center>
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For developers, this means building high-performance, real-time analytics applications without sacrificing SQL compatibility, transactional guarantees, or operational simplicity.
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$CLOUD_LONG delivers the best of $PG, optimized for real-time analytics.
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$CLOUD_LONG delivers the best of $PG, optimized for real-time analytics.
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[whitepaper_pdf]: https://assets.timescale.com/docs/downloads/tigerdata-whitepaper.pdf

api/_hyperfunctions/asap_smooth.md

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type: function
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api_details:
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summary: >
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Downsample your data with the [ASAP smoothing algorithm][asap-smoothing-algorithm].
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Downsample your data with the [ASAP smoothing algorithm](http://arxiv.org/pdf/1703.00983).
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This algorithm preserves the approximate shape and larger trends of the input data, while minimizing the local variance between points.
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signatures:
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- language: sql
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description: >
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An object representing a series of values occurring at set intervals from a starting time.
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It can be unpacked with `unnest`.
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For more information, see the documentation on [timevectors][timevectors].
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For more information, see the documentation on [timevectors](/use-timescale/:currentVersion:/hyperfunctions/function-pipelines/#timevectors).
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examples:
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- description: >
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This example uses a table called `metrics`, with columns for `date` and `reading`. The columns contain measurements that have been accumulated over a large interval of time.

api/_hyperfunctions/compact_state_agg/duration_in.md

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`running` state.
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If you prefer to see the result in seconds,
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[`EXTRACT`][extract]
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[`EXTRACT`](https://www.postgresql.org/docs/current/functions-datetime.html#FUNCTIONS-DATETIME-EXTRACT)
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the epoch from the returned result.
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command:
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code: |

api/_hyperfunctions/compact_state_agg/interpolated_duration_in.md

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for interpolation.
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If you prefer to see the result in seconds,
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[`EXTRACT`][extract]
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[`EXTRACT`](https://www.postgresql.org/docs/current/functions-datetime.html#FUNCTIONS-DATETIME-EXTRACT)
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the epoch from the returned result.
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command:
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api/_hyperfunctions/gp_lttb.md

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type: function
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api_details:
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summary: |
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Downsample your data with the [Largest Triangle Three Buckets algorithm][largest-triangle-three-buckets-algorithm], while preserving gaps in the underlying data.
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This method is a specialization of the [LTTB][lttb] algorithm.
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Downsample your data with the [Largest Triangle Three Buckets algorithm](https://github.com/sveinn-steinarsson/flot-downsample), while preserving gaps in the underlying data.
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This method is a specialization of the [LTTB](/api/:currentVersion:/hyperfunctions/downsampling/#lttb) algorithm.
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signatures:
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- language: sql
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code: |
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description: >
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An object representing a series of values occurring at set intervals from a starting time.
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It can be unpacked with `unnest`.
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For more information, see the documentation on [timevectors][timevectors].
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For more information, see the documentation on [timevectors](/use-timescale/:currentVersion:/hyperfunctions/function-pipelines/#timevectors).
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examples:
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- description: >
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This example uses a table with raw data generated as a sine wave, and removes a day from the middle of the data.

api/_hyperfunctions/lttb.md

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type: function
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api_details:
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summary: >
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Downsample your data with the [Largest Triangle Three Buckets algorithm][largest-triangle-three-buckets-algorithm].
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Downsample your data with the [Largest Triangle Three Buckets algorithm](https://github.com/sveinn-steinarsson/flot-downsample).
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This algorithm tries to retain visual similarity between the downsampled data and the original dataset.
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signatures:
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description: >
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An object representing a series of values occurring at set intervals from a starting time.
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It can be unpacked with `unnest`.
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For more information, see the documentation on [timevectors][timevectors].
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For more information, see the documentation on [timevectors](/use-timescale/:currentVersion:/hyperfunctions/function-pipelines/#timevectors).
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examples:
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- description: >
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This example uses a table with raw data generated as a sine wave.

api/_hyperfunctions/state_agg/duration_in.md

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`running` state.
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If you prefer to see the result in seconds,
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[`EXTRACT`][extract]
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[`EXTRACT`](https://www.postgresql.org/docs/current/functions-datetime.html#FUNCTIONS-DATETIME-EXTRACT)
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the epoch from the returned result.
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command:
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api/_hyperfunctions/state_agg/interpolated_duration_in.md

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for interpolation.
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If you prefer to see the result in seconds,
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[`EXTRACT`][extract]
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[`EXTRACT`](https://www.postgresql.org/docs/current/functions-datetime.html#FUNCTIONS-DATETIME-EXTRACT)
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the epoch from the returned result.
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api/_hyperfunctions/state_agg/timeline_agg.md

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summary: >
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Aggregate state data into a state aggregate to track state transitions.
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Unlike [`compact_state_agg`][compact_state_agg],
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Unlike [`compact_state_agg`](/api/:currentVersion:/hyperfunctions/state-tracking/compact_state_agg/),
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which only stores durations, `state_agg` also stores the timestamps of
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state transitions.
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signatures:

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