Abstract: A collar has a band having oppositely disposed first and second surfaces. Acoustic concentrators project from the first surface in a projection direction and are configured to penetrate fur in a portion of an animal to place the band in communication with the animal. Acoustic sensors functionally associated with the acoustic concentrators are configured to measure at least one first bioparameter by detecting vibrations corresponding to the at least one first bioparameter, and generate signals representing the at least one first bioparameter. Non-acoustic sensors are associated with the band and are configured to measure one or more second bioparameters associated with the animal, and generate signals representing the one or more second bioparameters. AGC circuitry adjusts signal gain of the signals representing the at least one first bioparameter. A processing subsystem determines a condition of the animal based at least in part by processing signals received from the AGC circuitry.

Abstract: A method for rapid data analysis includes receiving and interpreting a first query operating on a first dataset partitioned into shards by a first field; collecting a first data sample from a first set of data shards; calculating a first result to the first query based on analysis of the first data sample; and partitioning a second dataset into shards by a second field based on the first result.

Abstract: A method for rapid data analysis includes receiving and interpreting a first query operating on a first dataset partitioned into shards by a first field; collecting a first data sample from a first set of data shards; calculating a first result to the first query based on analysis of the first data sample; and partitioning a second dataset into shards by a second field based on the first result.

Abstract: A method for enhancing rapid data analysis includes receiving a set of data; storing the set of data in a first set of data shards sharded by a first field; and identifying anomalous data from the set of data by monitoring a range of shard indices associated with a first shard of the first set of data shards, detecting that the range of shard indices is smaller than an expected range by a threshold value, and identifying data of the first shard as anomalous data.

Abstract: A method for enhancing rapid data analysis includes receiving a set of data; storing the set of data in a first set of data shards sharded by a first field; and identifying anomalous data from the set of data by monitoring a range of shard indices associated with a first shard of the first set of data shards, detecting that the range of shard indices is smaller than an expected range by a threshold value, and identifying data of the first shard as anomalous data.

Abstract: An external system (e.g., a website) is associated with an event and includes an interface that allows users to interact with streams of content associated with a social networking system. The interface allows a user to provide posts about the event via the interface, where the posts are displayed in the interface and also in a social networking interface on social networking system in connection with the user and other users associated with that user. The user can view, via the interface on the external system, posts from all users that are provided via the interface (e.g., everyone watching the event), thereby increasing the likelihood that the posts are relevant to the event. The user can also view, via the interface, posts from users associated with the user via the social networking system (e.g., friends of the user), regardless of where those are posted.

Abstract: A method for enhancing rapid data analysis includes receiving a set of data; storing the set of data in a first set of data shards sharded by a first field; and identifying anomalous data from the set of data by monitoring a range of shard indices associated with a first shard of the first set of data shards, detecting that the range of shard indices is smaller than an expected range by a threshold value, and identifying data of the first shard as anomalous data.

Abstract: A method for rapid data analysis includes receiving and interpreting a first query operating on a first dataset partitioned into shards by a first field; collecting a first data sample from a first set of data shards; calculating a first result to the first query based on analysis of the first data sample; and partitioning a second dataset into shards by a second field based on the first result.

Abstract: A method for enhancing rapid data analysis includes receiving a set of data; storing the set of data in a first set of data shards sharded by a first field; and identifying anomalous data from the set of data by monitoring a range of shard indices associated with a first shard of the first set of data shards, detecting that the range of shard indices is smaller than an expected range by a threshold value, and identifying data of the first shard as anomalous data.

Abstract: A method for rapid data analysis includes receiving and interpreting a first query operating on a first dataset partitioned into shards by a first field; collecting a first data sample from a first set of data shards; calculating a first result to the first query based on analysis of the first data sample; and partitioning a second dataset into shards by a second field based on the first result.

Abstract: A method for enhancing rapid data analysis includes receiving a set of data; storing the set of data in a first set of data shards sharded by a first field; and identifying anomalous data from the set of data by monitoring a range of shard indices associated with a first shard of the first set of data shards, detecting that the range of shard indices is smaller than an expected range by a threshold value, and identifying data of the first shard as anomalous data.

Abstract: A method for enhancing rapid data analysis includes receiving a set of data; storing the set of data in a first set of data shards sharded by a first field; and identifying anomalous data from the set of data by monitoring a range of shard indices associated with a first shard of the first set of data shards, detecting that the range of shard indices is smaller than an expected range by a threshold value, and identifying data of the first shard as anomalous data.

Abstract: An external system (e.g., a website) is associated with an event and includes an interface that allows users to interact with streams of content associated with a social networking system. The interface allows a user to provide posts about the event via the interface, where the posts are displayed in the interface and also in a social networking interface on social networking system in connection with the user and other users associated with that user. The user can view, via the interface on the external system, posts from all users that are provided via the interface (e.g., everyone watching the event), thereby increasing the likelihood that the posts are relevant to the event. The user can also view, via the interface, posts from users associated with the user via the social networking system (e.g., friends of the user), regardless of where those are posted.

Abstract: A method for rapid data analysis includes receiving and interpreting a first query operating on a first dataset partitioned into shards by a first field; collecting a first data sample from a first set of data shards; calculating a first result to the first query based on analysis of the first data sample; and partitioning a second dataset into shards by a second field based on the first result.

Abstract: A method for rapid data analysis comprising receiving and interpreting a query, collecting a first data sample from the first set of data shards, calculating an intermediate result to the query based on analysis of the first data sample, identifying a second set of data shards based on the intermediate result, collecting a second data sample from the second set of data shards, and calculating a final result to the query based on analysis of the second data sample.

Abstract: Techniques provided herein allow for management of data. In various embodiments, systems and methods prune and retain data being managed by a data management system, where the managed data can include log data aggregated from one or more servers for analysis purposes. According to some embodiments, pruning can be triggered according to one or more constraints, such as the age of managed data (e.g., retain only 30 days of managed data) or the memory space required to store the managed data (e.g., retain only 100 GB worth of managed data). The constraints that trigger data pruning can be based on a data retention policy. When triggered, pruning can be performed on a fraction of the managed data stored based on the data retention policy (e.g., 3 days of full managed data, 27 days of pruned managed data). The pruning may be performed by sampling, at a desired rate, the managed data.

Abstract: Techniques provided herein allow for management of data. In various embodiments, systems and methods prune and retain data being managed by a data management system, where the managed data can include log data aggregated from one or more servers for analysis purposes. According to some embodiments, pruning can be triggered according to one or more constraints, such as the age of managed data (e.g., retain only 30 days of managed data) or the memory space required to store the managed data (e.g., retain only 100 GB worth of managed data). The constraints that trigger data pruning can be based on a data retention policy. When triggered, pruning can be performed on a fraction of the managed data stored based on the data retention policy (e.g., 3 days of full managed data, 27 days of pruned managed data). The pruning may be performed by sampling, at a desired rate, the managed data.

Abstract: An external system (e.g., a website) is associated with an event and includes an interface that allows users to interact with streams of content associated with a social networking system. The interface allows a user to provide posts about the event via the interface, where the posts are displayed in the interface and also in a social networking interface on social networking system in connection with the user and other users associated with that user. The user can view, via the interface on the external system, posts from all users that are provided via the interface (e.g., everyone watching the event), thereby increasing the likelihood that the posts are relevant to the event. The user can also view, via the interface, posts from users associated with the user via the social networking system (e.g., friends of the user), regardless of where those are posted.

Abstract: A method for enhancing rapid data analysis includes receiving a set of data; storing the set of data in a first set of data shards sharded by a first field; and identifying anomalous data from the set of data by monitoring a range of shard indices associated with a first shard of the first set of data shards, detecting that the range of shard indices is smaller than an expected range by a threshold value, and identifying data of the first shard as anomalous data.

Abstract: A method for rapid data analysis comprising receiving and interpreting a query, collecting a first data sample from the first set of data shards, calculating an intermediate result to the query based on analysis of the first data sample, identifying a second set of data shards based on the intermediate result, collecting a second data sample from the second set of data shards, and calculating a final result to the query based on analysis of the second data sample.