Abstract: A load balancer allocates requests to a pool of web servers configured to have low queue capacities. If the queue capacity of a web server is reached, the web server responds to an additional request with a rejection notification to the load balancer, which enables the load balancer to quickly send the rejected request to another web server. Each web server self-monitors its rejection rate. If the rejection rate exceeds a threshold, the number of processes concurrently running on the web server is increased. If the rejection rate falls below a threshold, the number of processes concurrently running on the web server is decreased.

Abstract: A load balancer allocates requests to a pool of web servers configured to have low queue capacities. If the queue capacity of a web server is reached, the web server responds to an additional request with a rejection notification to the load balancer, which enables the load balancer to quickly send the rejected request to another web server. Each web server self-monitors its rejection rate. If the rejection rate exceeds a threshold, the number of processes concurrently running on the web server is increased. If the rejection rate falls below a threshold, the number of processes concurrently running on the web server is decreased.

Abstract: A load balancer allocates requests to a pool of web servers configured to have low queue capacities. If the queue capacity of a web server is reached, the web server responds to an additional request with a rejection notification to the load balancer, which enables the load balancer to quickly send the rejected request to another web server. Each web server self-monitors its rejection rate. If the rejection rate exceeds a threshold, the number of processes concurrently running on the web server is increased. If the rejection rate falls below a threshold, the number of processes concurrently running on the web server is decreased.

Abstract: A load balancer allocates requests to a pool of web servers configured to have low queue capacities. If the queue capacity of a web server is reached, the web server responds to an additional request with a rejection notification to the load balancer, which enables the load balancer to quickly send the rejected request to another web server. Each web server self-monitors its rejection rate. If the rejection rate exceeds a threshold, the number of processes concurrently running on the web server is increased. If the rejection rate falls below a threshold, the number of processes concurrently running on the web server is decreased.

Abstract: A variety of methods for improving efficiency in a database system are provided. In one embodiment, a method may comprise: generating multiple levels of data according to how recently the data have been updated, whereby most recently updated data are assigned to the newest level; storing each level of data in a specific storage tier; splitting data stored in a particular storage tier into two or more groups according to access statistics of each specific data; during compaction, storing data from different groups in separate data blocks of the particular storage tier; and when a particular data in a specific data block is requested, reading the specific data block into a low-latency storage tier.

Abstract: A load balancer allocates requests to a pool of web servers configured to have low queue capacities. If the queue capacity of a web server is reached, the web server responds to an additional request with a rejection notification to the load balancer, which enables the load balancer to quickly send the rejected request to another web server. Each web server self-monitors its rejection rate. If the rejection rate exceeds a threshold, the number of processes concurrently running on the web server is increased. If the rejection rate falls below a threshold, the number of processes concurrently running on the web server is decreased.

Abstract: A load balancer allocates requests to a pool of web servers configured to have low queue capacities. If the queue capacity of a web server is reached, the web server responds to an additional request with a rejection notification to the load balancer, which enables the load balancer to quickly send the rejected request to another web server. Each web server self-monitors its rejection rate. If the rejection rate exceeds a threshold, the number of processes concurrently running on the web server is increased. If the rejection rate falls below a threshold, the number of processes concurrently running on the web server is decreased.

Abstract: A variety of methods for improving efficiency in a database system are provided. In one embodiment, a method may comprise: generating multiple levels of data according to how recently the data have been updated, whereby most recently updated data are assigned to the newest level; storing each level of data in a specific storage tier; splitting data stored in a particular storage tier into two or more groups according to access statistics of each specific data; during compaction, storing data from different groups in separate data blocks of the particular storage tier; and when a particular data in a specific data block is requested, reading the specific data block into a low-latency storage tier.

Abstract: A load balancer allocates requests to a pool of web servers configured to have low queue capacities. If the queue capacity of a web server is reached, the web server responds to an additional request with a rejection notification to the load balancer, which enables the load balancer to quickly send the rejected request to another web server. Each web server self-monitors its rejection rate. If the rejection rate exceeds a threshold, the number of processes concurrently running on the web server is increased. If the rejection rate falls below a threshold, the number of processes concurrently running on the web server is decreased.

Abstract: A data object management scheme for storing a large plurality of small data objects (e.g., image files) in small number of large object stack file for storage in secondary storage (e.g., hard disks). By storing many individual data objects in a single object stack file, the number of files stored in the secondary storage is reduced by several orders of magnitude, from the billions or millions to the hundreds or so. Index data for each object stack file is generated and stored in primary storage to allow efficient and prompt access to the data objects. Requests to store or retrieve the data objects are made using HTTP messages including file identifiers that identify the files storing the data objects and keys identifying the data objects. A file server stores or retrieves the data object from secondary storage of a file server without converting the requests to NSF or POSIX commands.

Abstract: A data object management scheme for storing a large plurality of small data objects (e.g., image files) in small number of large object stack file for storage in secondary storage (e.g., hard disks). By storing many individual data objects in a single object stack file, the number of files stored in the secondary storage is reduced by several orders of magnitude, from the billions or millions to the hundreds or so. Index data for each object stack file is generated and stored in primary storage to allow efficient and prompt access to the data objects. Requests to store or retrieve the data objects are made using HTTP messages including file identifiers that identify the files storing the data objects and keys identifying the data objects. A file server stores or retrieves the data object from secondary storage of a file server without converting the requests to NSF or POSIX commands.

Abstract: A data object management scheme for storing a large plurality of small data objects (e.g., image files) in small number of large object stack file for storage in secondary storage (e.g., hard disks). By storing many individual data objects in a single object stack file, the number of files stored in the secondary storage is reduced by several orders of magnitude, from the billions or millions to the hundreds or so. Index data for each object stack file is generated and stored in primary storage to allow efficient and prompt access to the data objects. Requests to store or retrieve the data objects are made using HTTP messages including file identifiers that identify the files storing the data objects and keys identifying the data objects. A file server stores or retrieves the data object from secondary storage of a file server without converting the requests to NSF or POSIX commands.

Abstract: A load balancer allocates requests to a pool of web servers configured to have low queue capacities. If the queue capacity of a web server is reached, the web server responds to an additional request with a rejection notification to the load balancer, which enables the load balancer to quickly send the rejected request to another web server. Each web server self-monitors its rejection rate. If the rejection rate exceeds a threshold, the number of processes concurrently running on the web server is increased. If the rejection rate falls below a threshold, the number of processes concurrently running on the web server is decreased.