数据点Data Point:数据源在某个时间产生的某个量测指标值(Field Value)称为一个数据点,数据库查询、写入时按数据点数来作为统计指标; 时间线 Time Series:数据源的某一个指标随时间变化,形成时间线,Metric + Tags + Field 组合确定一条时间线;针对时序数据的计算包括降采样、聚合(sum、count、max、min等)、插...
SyntheticControlChartTimeSeriesDataSet(合成控 制图表时间序列数据集) 数据摘要: Thisdataconsistsofsyntheticallygeneratedcontrolcharts. 中文关键词: 合成控制图表,时间序列,分类,聚类,UCI, 英文关键词: SyntheticControlChart,Time-Series,Classification,Clustering,UCI, 数据格式: TEXT 数据用途: Thisdatasetisusedforclass...
timeseriesKey := tablestore.NewTimeseriesKey() timeseriesKey.SetMeasurementName("CPU") timeseriesKey.SetDataSource("127.0.0.1") timeseriesKey.AddTag("City" , "Hangzhou") timeseriesKey.AddTag("Region" , "Xihu") timeseriesRow := tablestore.NewTimeseriesRow(timeseriesKey) timeseriesRow.SetTim...
Time series data is special — not just in the unique data that it captures, but also in the ways we interact with that data. Maybe you’re starting to use time series data from sensors in your company’s thermostats (to finally prove that Dad is turning down the temperature at night)...
Setting thegranularityparameter accurately improves performance by optimizing how data in the time series collection is stored internally. To set the parameter accurately, choose agranularityvalue that is closest to the ingestion rate for a unique data source as specified by the value for themetaField...
tunnel = pd.read_csv(data_dir / "tunnel.csv", parse_dates=["Day"]) tunnel = tunnel.set_index("Day").to_period() 让我们做一个移动平均线图,看看这个序列有什么样的趋势。由于这个序列有每日观察,让我们选择一个 365 天的窗口来平滑一年内的任何短期变化。
# loading the data. tunnel = tunnel.set_index("Day") # By default, Pandas creates a `DatetimeIndex` with dtype `Timestamp` # (equivalent to `np.datetime64`, representing a time series as a # sequence of measurements taken at single moments. A `PeriodIndex`, ...
TB级别time series data的索引和挖掘 编者对文章的总结 本文基于SAX提出了iSAX,是对时间序列的一种抽象表示法,可以动态扩展其维度,以此构造树形结构的索引。这种索引主要的功能是应对相似搜索(similarty search),其它功能作者并未提及。在similarty search中,近似结果的获得是非常快的,在秒的级别;精确结果的搜索性能则...
TSDBisthe abilitytofilter measurementsusingtags.Eachdata pointislabeledwitha tag that adds context information, suchaswherethe measurement was taken.Withtime series data, the data often contain more than asingleseries,andisasetofmultiple time series. Many Grafana data sources support this typeofdata...
Delving a bit deeper, you might analyze time series data with technical analysis tools to know whether the stock’s time series shows any seasonality. This will help to determine if the stock goes through peaks and troughs at regular times each year. Analysis in this area would require taking...