公开(公告)号：US20170091334A1

公开(公告)日：2017-03-30

申请号：US14869656

申请日：2015-09-29

Applicant: Facebook, Inc.

Inventor： Igor Kabiljo ,  Laxman Dhulipala ,  Alon Michael Shalita ,  Arun Dattaram Sharma ,  Brian Christopher Karrer

IPC: G06F17/30

CPC classification number: G06F17/30867 ,  G06F17/3053 ,  G06F17/30584 ,  G06F17/30876 ,  G06F17/30958 ,  G06F17/30961

Abstract: Embodiments are disclosed for improving cache or memory efficiency of a social network system. A method according to some embodiments includes steps of: receiving an instruction to improve cache or memory efficiency of social graph data of a social graph; generating based on the social graph a partitioning tree including multiple bottom-level buckets, the partitioning tree dividing the vertices of the social graph into the bottom-level buckets and ordering the bottom-level buckets such that a social network metric regarding the vertices is optimized; assigning user IDs to the vertices of the social network in a numerical sequence based on the ordering of the bottom-level buckets; storing the social graph data of the users in storage locations in an order according to the numeral sequence of the assigned user IDs of the vertices.

公开(公告)号：US10025867B2

公开(公告)日：2018-07-17

申请号：US14869656

申请日：2015-09-29

Applicant: Facebook, Inc.

Inventor： Igor Kabiljo ,  Laxman Dhulipala ,  Alon Michael Shalita ,  Arun Dattaram Sharma ,  Brian Christopher Karrer

IPC: G06F17/30

Abstract: Embodiments are disclosed for improving cache or memory efficiency of a social network system. A method according to some embodiments includes steps of: receiving an instruction to improve cache or memory efficiency of social graph data of a social graph; generating based on the social graph a partitioning tree including multiple bottom-level buckets, the partitioning tree dividing the vertices of the social graph into the bottom-level buckets and ordering the bottom-level buckets such that a social network metric regarding the vertices is optimized; assigning user IDs to the vertices of the social network in a numerical sequence based on the ordering of the bottom-level buckets; storing the social graph data of the users in storage locations in an order according to the numeral sequence of the assigned user IDs of the vertices.

公开(公告)号：US20160087880A1

公开(公告)日：2016-03-24

申请号：US14491771

申请日：2014-09-19

Applicant: Facebook, Inc.

Inventor： Alon Michael Shalita ,  Igor Kabiljo ,  Kenneth Lau ,  Arun Dattaram Sharma ,  Alexander Michael Laslavic

IPC: H04L12/721 ,  H04L29/08 ,  H04L12/927

CPC classification number: H04L67/1097 ,  H04L45/306 ,  H04L67/1021 ,  H04L67/2842

Abstract: A technology for routing traffic from similar users to a same server cluster to improve data center efficiency is disclosed. When a traffic routing server receives a request from a user, the traffic routing server determines an identifier of a partition to which the user is assigned. The user and many other users with whom the user shares a social attribute are co-located in the same partition. The traffic routing server then computes a hash of the identifier using a hash function and locates a server cluster on a consistent hash ring using the computed hash. The traffic routing server then sends the request from the user to that server cluster. By consistently sending requests from users assigned to the same partition to the same server cluster, the technology improves cache hit rates and reduces data duplication across the server clusters, which in turn improves datacenter efficiency.

Abstract translation: 公开了一种用于将流量从类似用户路由到同一服务器集群以提高数据中心效率的技术。 当流量路由服务器接收到来自用户的请求时，流量路由服务器确定分配给用户的分区的标识符。 用户和与用户共享社交属性的许多其他用户共同位于同一分区中。 然后，流量路由服务器使用散列函数计算标识符的散列，并使用计算的散列将服务器集群定位在一致的散列环上。 然后，流量路由服务器将请求从用户发送到该服务器集群。 通过一致地将分配给同一分区的用户的请求发送到同一个服务器集群，该技术可以提高缓存命中率，并减少服务器集群的数据重复，从而提高数据中心的效率。

公开(公告)号：US09860316B2

公开(公告)日：2018-01-02

申请号：US14491771

申请日：2014-09-19

Applicant: Facebook, Inc.

Inventor： Alon Michael Shalita ,  Igor Kabiljo ,  Kenneth Lau ,  Arun Dattaram Sharma ,  Alexander Michael Laslavic

IPC: G06F15/167 ,  H04L29/08 ,  H04L12/725

CPC classification number: H04L67/1097 ,  H04L45/306 ,  H04L67/1021 ,  H04L67/2842

Abstract: A technology for routing traffic from similar users to a same server cluster to improve data center efficiency is disclosed. When a traffic routing server receives a request from a user, the traffic routing server determines an identifier of a partition to which the user is assigned. The user and many other users with whom the user shares a social attribute are co-located in the same partition. The traffic routing server then computes a hash of the identifier using a hash function and locates a server cluster on a consistent hash ring using the computed hash. The traffic routing server then sends the request from the user to that server cluster. By consistently sending requests from users assigned to the same partition to the same server cluster, the technology improves cache hit rates and reduces data duplication across the server clusters, which in turn improves datacenter efficiency.

公开(公告)号：US20140156566A1

公开(公告)日：2014-06-05

申请号：US13689969

申请日：2012-11-30

Applicant: Facebook, Inc.

Inventor： Igor Kabiljo ,  Aleksandar Ilic ,  Ming Hua ,  Hong Yan

IPC: G06N99/00

CPC classification number: G06N99/005 ,  G06Q30/02 ,  G06Q50/01

Abstract: Online systems generate predictors for predicting actions of users of the online system. The online system receives requests to generate predictor models for predicting whether a user is likely to take an action of a particular action type. The request specifies the type of action and criteria for identifying a successful instance of the action type and a failure instance of the action type. The online system collects data including successful and failure instances of the action type. The online system generates one or more predictors of different types using the generated data. The online system evaluates and compares the performance of the different predictors generated and selects a predictor based on the performance. The online system returns a handle to access the generated predictor to the requester of the predictor.

Abstract translation: 在线系统生成用于预测在线系统用户的动作的预测因子。 在线系统接收生成用于预测用户是否可能采取特定动作类型的动作的预测器模型的请求。 请求指定用于标识操作类型的成功实例的动作类型和标准，以及动作类型的失败实例。 在线系统收集数据，包括操作类型的成功和失败实例。 在线系统使用生成的数据生成不同类型的一个或多个预测变量。 在线系统评估并比较生成的不同预测变量的性能，并根据性能选择预测变量。 在线系统返回一个句柄来访问生成的预测变量到预测变量的请求者。