Optionaloptions: ViewOptions<S>Example: view.bisect(new Time(t)). Insertion index for key in the sorted view buffer (binary search).
Example: view.column('cpu').toFloat64Array(). Gathers a numeric
value column from the view's current events. Restricted to numeric
columns (the chart-feed case) — string / array columns are rejected
at compile time; read the partition key as a scalar via
at(i).get(name), or toTimeSeries() for full kind coverage.
Example: live.window('1m').count(). Returns the number of
events currently in the view's buffer. For windows created via
window(duration), this is "events in the last N seconds";
for window(count), it's "events in the last N retained."
Cheap O(1) accessor that reads this.length directly — same
value as view.length. Provided as a method so it composes
naturally with LiveView.rate.
Example: live.window('1m').eventRate(). Returns events per
second over the view's window — count() / windowSeconds.
Only defined on time-based windows. Throws on count-based
windows (window(100)) and on views that weren't created by
a .window(duration) call (filter / map / select on a
non-windowed source — there's no denominator to use).
Convenient for metrics-endpoint gauges and React displays ("EVENT RATE 8.0/s"). Pairs with LiveView.count for cases where both numbers are needed.
Distinct from LiveView.rate, which is the per-column
derivative operator (rate-of-change of values).
eventRate is per-window-events-per-second; rate(columns)
is per-event derivative of the named columns.
Example: view.every(e => e.get('healthy')).
Optionaloptions: { limit?: number }Example: view.find(e => e.get('value') > 0).
Example: view.keyColumn().begin. Gathers the time axis into a
TimeKeyColumn directly from the view's current events.
Time-keyed series only.
Per-event transform. Each source event is run through fn and
the result is appended to the view's buffer. The view does NOT
re-sort by key — events flow through in source order, which
preserves the upstream's sort invariant only if fn returns
events with the same key.
If fn rewrites the event's key (e.g. shifting timestamps,
changing the interval), the view's buffer is no longer
key-sorted. The Tier 2 query primitives (LiveView.bisect,
LiveView.includesKey, LiveView.atOrBefore,
LiveView.atOrAfter) all assume sorted-by-key and will
return wrong answers on a re-keying map. Use map only for
data transforms; use a separate live primitive for time-axis
transforms.
Walk-now partition read. Buckets the view's current events by col
and runs fn over each partition's column view, returning a Map
keyed by the partition value (normalized to a string, matching
TimeSeries.partitionBy(col).toMap(fn)) — but skipping the
per-partition TimeSeries construction (gathers only the columns
fn reads). Distinct from LiveSeries.partitionBy, which is
subscription-oriented (live sub-series); this is a snapshot-style
read of the current window.
Streaming reduce over the view's current buffer. See LiveSeries.reduce for the full surface.
Optionaloptions: LiveRollingOptionsOptionaloptions: LiveRollingOptionsKeyed-form fused multi-window rolling on a LiveView. See
LiveSeries.rolling for the full surface — chained-from-
a-view behavior is identical to the same call on a top-level
LiveSeries.
Optionaloptions: LiveRollingOptionsBounded-memory stream sampling on a LiveView. Same semantics as
LiveSeries.sample — stride only on the live side in v0.17.0.
Multi-entity bias trap applies here too: a LiveView derived
from a multi-entity source carries the same bias risk. Chain after
partitionBy(...) for the safe-by-construction shape; see
LiveSeries.sample for the full discussion.
Example: view.some(e => e.get('healthy')).
Optionalname: string
Example:
view.atOrAfter(new Time(t)).