公开(公告)号：US20180039555A1

公开(公告)日：2018-02-08

申请号：US15609938

申请日：2017-05-31

Applicant: Oracle International Corporation

Inventor： Sampanna Shahaji Salunke ,  Dustin Garvey ,  Uri Shaft ,  Maria Kaval

IPC: G06F11/34 ,  G06F11/30 ,  G06F11/32

CPC classification number: G06F11/3409 ,  G06F11/00 ,  G06F11/3034 ,  G06F11/3065 ,  G06F11/327

Abstract: Systems and methods for performing unsupervised baselining and anomaly detection using time-series data are described. In one or more embodiments, a baselining and anomaly detection system receives a set of time-series data. Based on the set of time-series, the system generates a first interval that represents a first distribution of sample values associated with the first seasonal pattern and a second interval that represents a second distribution of sample values associated with the second seasonal pattern. The system then monitors a time-series signals using the first interval during a first time period and the second interval during a second time period. In response to detecting an anomaly in the first seasonal pattern or the second seasonal pattern, the system generates an alert.

公开(公告)号：US20170249648A1

公开(公告)日：2017-08-31

申请号：US15266971

申请日：2016-09-15

Applicant: Oracle International Corporation

Inventor： Dustin Garvey ,  Uri Shaft ,  Edwina Ming-Yue Lu ,  Sampanna Shahaji Salunke ,  Lik Wong

IPC: G06Q30/02

CPC classification number: G06T11/206 ,  G06F17/18 ,  G06F21/55 ,  G06K9/00536 ,  G06K9/628 ,  G06N20/00 ,  G06Q10/04 ,  G06Q10/06 ,  G06Q10/0631 ,  G06Q10/06315 ,  G06Q10/1093 ,  G06Q30/0202 ,  G06T11/001

Abstract: Techniques are described for generating seasonal forecasts. According to an embodiment, a set of time-series data is associated with one or more classes, which may include a first class that represent a dense pattern that repeats over multiple instances of a season in the set of time-series data and a second class that represent another pattern that repeats over multiple instances of the season in the set of time-series data. A particular class of data is associated with at least two sub-classes of data, where a first sub-class represents high data points from the first class, and a second sub-class represents another set of data points from the first class. A trend rate is determined for a particular sub-class. Based at least in part on the trend rate, a forecast is generated.

公开(公告)号：US09582367B2

公开(公告)日：2017-02-28

申请号：US13721895

申请日：2012-12-20

Applicant: Oracle International Corporation

Inventor： George An ,  Pete Belknap ,  Uri Shaft ,  Benoit Dageville ,  Ameet Kini

IPC: G06F17/30 ,  G06F11/14 ,  G06F11/32

CPC classification number: G06F11/1435 ,  G06F11/321 ,  G06F11/323 ,  G06F17/30424

Abstract: A method for obtaining data items from an unresponsive database host. The method includes receiving an indication that the database host is unresponsive, receiving, from a management server via a diagnostic connection, a first request for a first organized data item, and sending a first query, using a first interface, to a memory for the first organized data item. The method further includes receiving, from the management server via a normal connection, a second request for a second organized data item, retrieving, from memory on the database host, a first data item in response to the first query, converting the first data item into the first organized data item, and sending the first organized data item to the management server, wherein the first organized data item is analyzed to determine a source causing the database host to be unresponsive.

Abstract translation: 一种从无响应数据库主机获取数据项的方法。 该方法包括接收数据库主机不响应的指示，从管理服务器经由诊断连接接收对第一组织数据项的第一请求，以及使用第一接口向存储器发送第一查询 首先组织的数据项。 该方法还包括从管理服务器经由正常连接接收对第二组织数据项的第二请求，从数据库主机上的存储器检索响应于第一查询的第一数据项，转换第一数据项 进入第一组织数据项，并将第一组织数据项发送到管理服务器，其中分析第一组织数据项以确定导致数据库主机无响应的源。

公开(公告)号：US20160092134A1

公开(公告)日：2016-03-31

申请号：US14865476

申请日：2015-09-25

Applicant: Oracle International Corporation

Inventor： John Raitto ,  Uri Shaft

IPC: G06F3/06 ,  G06F12/08

CPC classification number: G06F3/0673 ,  G06F3/0608 ,  G06F3/0632 ,  G06F3/0638 ,  G06F16/283

Abstract: According to an embodiment, storage configurations are identified for storing items, such as database tables, partitions, or any other types of objects or data structures, within a desired storage area, such as an in-memory data store or any other limited storage resource. Each of the storage configurations is assigned to a particular item of the items. Each of the storage configurations associates the assigned particular item with one or more storage configuration options. Storage recommendations are generated for at least a set of the storage configurations. A different storage recommendation exists for each storage configuration in the set of the storage configurations. The storage recommendation associates the storage configuration with a range of possible storage sizes for a particular storage area of a system. Based on the storage recommendations, recommended system configurations a generated for different possible storage sizes of the particular storage area.

Abstract translation: 根据实施例，存储配置被识别用于在期望的存储区域（诸如存储器内数据存储器或任何其他有限的存储资源）内存储诸如数据库表，分区或任何其它类型的对象或数据结构之类的项目 。 每个存储配置被分配给项目的特定项目。 每个存储配置将分配的特定项目与一个或多个存储配置选项相关联。 为至少一组存储配置生成存储建议。 对存储配置集中的每个存储配置存在不同的存储建议。 存储建议将存储配置与系统的特定存储区域的可能存储大小的范围相关联。 根据存储建议，为特定存储区域的不同可能的存储大小生成推荐的系统配置。

公开(公告)号：US20140089270A1

公开(公告)日：2014-03-27

申请号：US13627906

申请日：2012-09-26

Applicant: Oracle International Corporation

Inventor： Uri Shaft ,  Graham Stephen Wood ,  John Beresniewicz

IPC: G06F17/30

CPC classification number: G06F17/30371 ,  G06F17/30306

Abstract: A method for determining event counts for a database system includes capturing samples for the active sessions based on a pre-defined sampling frequency and identifying events from the captured samples. The method further includes determining the wait time for each of the identified events and determining an event count for the active sessions using a harmonic mean. The harmonic mean is a summation of the maximum of either one or the ratio of the sampling frequency to the determined wait time for each of the identified events.

Abstract translation: 用于确定数据库系统的事件计数的方法包括基于预定义的采样频率捕获活动会话的采样，并从捕获的采样中识别事件。 该方法还包括确定每个识别的事件的等待时间，并使用谐波均值确定活动会话的事件计数。 谐波平均值是每个识别事件中的任一个的最大值或采样频率与所确定的等待时间的比率的总和。