Tabular DB interface for unstructured data

    公开(公告)号:US09760571B1

    公开(公告)日:2017-09-12

    申请号:US14338634

    申请日:2014-07-23

    IPC分类号: G06F17/30

    CPC分类号: G06F17/30011

    摘要: A tabular (relational) DB interface is responsive to SQL commands for accessing unstructured data bases. An application receives a relational data command or query and maps fields from the relational query to fields in an unstructured data store including documents arranged in a hierarchy and unbounded by fixed types or field lengths. The application generates field names by concatenating nested hierarchy field names to define unique “flat file” field names in a tabular form. The application generates a catalog defining the mapping which is used as metadata for accessing the unstructured data to satisfy the relational query. Use of the metadata avoids copying or translating the unstructured data store to a tabular form because the unstructured data collection remains unmodified, and is accessed via the catalog.

    Columnar storage and processing of unstructured data

    公开(公告)号:US11144580B1

    公开(公告)日:2021-10-12

    申请号:US14304497

    申请日:2014-06-13

    IPC分类号: G06F16/35

    摘要: Data storage for unstructured data such as JSON data stored as collections of documents transforms the JSON data into a columnar form of storing unstructured data by grouping similar fields together for facilitating retrieval of the individual fields from a range of documents. Groups of fields are stored in individual files for each field. Compound data such as arrays and subdocuments are also broken down into files for each atomic field. In other words, a compound document structure that defines a hierarchy or “tree” of fields is flattened such that each “leaf” of the tree is stored in a separate file.

    Unstructured database analytics processing

    公开(公告)号:US10373058B1

    公开(公告)日:2019-08-06

    申请号:US14264413

    申请日:2014-04-29

    摘要: An analytics processing system generates analytics from a collection of unstructured data by identifying trends in the data and deriving associations or correlations between series of values. Each series is generated from a set of field labeled values in the set, and compared to other series in the collection. Identified relationships in the series are scored based on depiction of an illustrative, predictive, or non-random association, and ranked by a scoring metric for analytical value. A visualization of the relationships are ranked and rendered such that the visualization highlights the association in a manner not achievable by simple inspection of the field values. Relationships are graphed by lines, circles, bars (histogram) on labeled axes based on the series. In this manner, a user may generate analytic results from a large data set, and pinpoint significant associations by paging through renderings scored as the most illustrative of notable trends.

    Processor for database analytics processing

    公开(公告)号:US09830369B1

    公开(公告)日:2017-11-28

    申请号:US14276135

    申请日:2014-05-13

    IPC分类号: G06F17/30

    摘要: An analytics processing system generates analytics from a collection of unstructured data by. transforming a received source of input data from an unstructured database into a delimiterless form, and iteratively moving portions of the delimiterlesss input data from a solid-state memory to a shared memory adapted for parallel operations with a plurality of GPU cores. The method stores computational data, such as values for matching, in a high speed memory responsive to operations with the shared memory, in which the high-speed memory remains static for the duration of the iterations. A host CPU invokes the plurality of cores for performing the parallel operations on the computational data and the portions of the delimiterless input data, and stores a result in a general memory accessible from a graphical user interface (GUI). The GPU cores parallelize the matching task of the input data from the unstructured database against the match data.

    Identifying attribute propagation for multi-tier processing
    9.
    发明申请
    Identifying attribute propagation for multi-tier processing 有权
    识别多层处理的属性传播

    公开(公告)号:US20100132024A1

    公开(公告)日:2010-05-27

    申请号:US11642432

    申请日:2006-12-20

    CPC分类号: G06F9/545 G06F2209/542

    摘要: A multi-tier attribute tracking mechanism provides the ability to identify the end user credentials and other client information and attributes and assign them to database requests in an application server architecture. Disclosed configurations identify the processing unit, or thread, assigned by the operating system to service the incoming request from the user at the application tier. A matching of users to threads allows successive thread activity to be mapped back to the initiating user. Conventional interception of database access attempts at the application level (so called “server taps,” or staps) identified only the database user (the account in the database) and associated connection as the responsible user. By intercepting, or “tapping” the access request at the operating system level (using so-called kernel taps, or “ktaps”), the mechanism matches which application requests map to which database requests. With this matching, the database requests can be tagged with the user credentials which are known through the application request.

    摘要翻译: 多层属性跟踪机制提供了识别最终用户凭据和其他客户端信息和属性的能力,并将其分配给应用程序服务器体系结构中的数据库请求。 所公开的配置标识由操作系统分配的处理单元或线程,以在应用层对来自用户的传入请求进行服务。 用户与线程的匹配允许连续的线程活动被映射回发起用户。 在应用程序级(即所谓的“服务器分接”或“数据库”)的数据库访问尝试的常规拦截仅将数据库用户(数据库中的帐户)和相关连接标识为负责用户。 通过在操作系统级别拦截或“敲击”访问请求(使用所谓的内核抽头或“ktaps”),该机制将匹配哪个应用程序请求映射到哪个数据库请求。 通过这种匹配,数据库请求可以通过应用程序请求已知的用户凭据进行标记。

    Identifying attribute propagation for multi-tier processing
    10.
    发明授权
    Identifying attribute propagation for multi-tier processing 有权
    识别多层处理的属性传播

    公开(公告)号:US08141100B2

    公开(公告)日:2012-03-20

    申请号:US11642432

    申请日:2006-12-20

    IPC分类号: G06F15/163

    CPC分类号: G06F9/545 G06F2209/542

    摘要: A multi-tier attribute tracking mechanism identifies end user credentials and other client information and attributes and assigns them to database requests in an application server architecture. Disclosed configurations identify the processing unit, or thread, assigned by the operating system to service the incoming request from the user at the application tier. A matching of users to threads allows successive thread activity to be mapped back to the initiating user. Conventional interception of database access attempts at the application level (“server taps,” or staps) identified only the database user (the account in the database) and associated connection as the responsible user. By intercepting, or “tapping” the access request at the operating system level (using kernel taps, or “ktaps”), the mechanism matches which application requests map to which database requests. With this matching, the database requests can be tagged with the user credentials which are known through the application request.

    摘要翻译: 多层属性跟踪机制识别最终用户凭据和其他客户端信息和属性,并将其分配给应用程序服务器体系结构中的数据库请求。 所公开的配置标识由操作系统分配的处理单元或线程,以在应用层对来自用户的传入请求进行服务。 用户与线程的匹配允许连续的线程活动被映射回发起用户。 在应用程序级别(“服务器轻击”或“数据库”)的常规拦截数据库访问尝试仅将数据库用户(数据库中的帐户)和相关连接标识为负责用户。 通过在操作系统级别拦截或“敲击”访问请求(使用内核分接头或“ktaps”),该机制将哪个应用程序请求映射到哪个数据库请求。 通过这种匹配,数据库请求可以通过应用程序请求已知的用户凭据进行标记。