Implement timeSeriesDerivToGrid and timeSeriesPredictLinearToGrid

[stephchi0]

Aggregate functions timeSeriesDerivToGrid and timeSeriesPredictLinearToGrid.
Behaves similarly to timeSeriesRateToGrid, accepting parameters for start timestamp, end timestamp, step, and look back window (predict_linear accepting an additional predict_offset parameter), as well as two arguments for the timestamps and values.
Returns a derivative or prediction value using least-square linear regression, calculated on samples in the specified window for each timestamp in the time grid defined by the parameters. The return type is Array(Nullable(Float64)).

Changelog category (leave one):

• New Feature

Changelog entry (a user-readable short description of the changes that goes into CHANGELOG.md):

timeSeriesDerivToGrid and timeSeriesPredictLinearToGrid aggregate functions to re-sample data to a time grid defined by the specified start timestamp, end timestamp, and step; calculates PromQL-like deriv and predict_linear, respectively.

Documentation entry for user-facing changes

• Documentation is written (mandatory for new features)

[CLAassistant]

All committers have signed the CLA.

[clickhouse-gh]

Workflow [PR], commit [10651a6]

[vitlibar]

CI failures are unrelated:

• Logical error: '(isConst() || isSparse()) ? getDataType() == rhs.getDataType() : typeid(*this) == typeid(rhs)' - see issue 83847
• Logical error: 'ReadBuffer is canceled. Can't read from it.' - see issue 84186