Provided for is a system for processing rich time-series data. Such a system may comprise an Application Programming Interface (API) subsystem, the API subsystem providing an interface for a third-party data source to transmit data. The system may further include a data receiver subsystem, the data receiver subsystem configured to verify the incoming data, said verification comprising authenticating whether the incoming data is rich time-series data. Further, the system may include a data processor subsystem, a database subsystem configured to store data, and a monitoring subsystem configured to transmit one or more alerts.

An output method executed by a computer includes: receiving compressed data encoded in a state in which a page break is identifiable in print data having a plurality of pages and an encoding dictionary used for the encoding; identifying the page break of the received compressed data and partially decompressing the received compressed data into the print data in units of pages, by using the encoding dictionary; and outputting the print data in order of the decompression.

A field-programmable gate array (FPGA)-based FAST protocol decoding method, apparatus, and device, and a readable storage medium. The method acquires an actual XML template in real time and analyzes the actual XML template, generates a FAST protocol intermediate representation, and determines, according to preset decoding parameters, the maximum number of fields which are read at a single time, so as to generate a field matching state machine. Thus, the present disclosure can support a dynamically updated XML template, and allows flexible setting of the maximum number of fields according to an actual network bandwidth, and is applicable to disclosure scenarios of different network bandwidths. In a decoding process, the present disclosure realizes, by means of a field shift register and the field matching state machine, the function of reading and decoding a plurality of fields in parallel each time, significantly improving decoding efficiency.

Systems and methods for lossless compression of tabular numeric data are provided. The system can include one or more data compression servers executing data compression system code to compress the tabular numeric data, a storage database to store the compressed tabular numeric data, and one or more data decompression servers to decompress the tabular numeric data for use. The one or more data compression servers, the storage database, and the one or more data decompression servers can communicate via a communication network. The system can receive the uncompressed tabular numeric data from one or more data generation systems, processes the uncompressed tabular numeric data with the data compression system code, and generate a compressed table of numeric information, which can be stored in the database, or later decompressed by the one or more data decompression servers.

Unsorted sparse dictionary encodings are transformed into unsorted-dense or sorted-dense dictionary encodings. Sparse domain codes have large gaps between codes that are adjacent in order. Unlike spare codes, dense codes have smaller gaps between adjacent codes; consecutive codes are dense codes that have no gaps between adjacent codes. The techniques described herein are relational approaches that may be used to generate sparse composite codes and sorted codes.

Techniques described herein may be utilized to serialise and de-serialise arithmetic circuits that are utilized in the execution of computer programs. The arithmetic circuit may be utilized to build a Quadratic Arithmetic Problem (QAP) that is compiled into a set of cryptographic routines for a client and a prover. The client and prover may utilize a protocol to delegate execution of a program to the prover in a manner that allows the client to efficiently verify the prover correctly executed the program. The arithmetic circuit may comprise a set of symbols (e.g., arithmetic gates and values) that is compressed to produce a serialised circuit comprising a set of codes, wherein the set of symbols is derivable from the set of codes in a lossless manner. Serialisation and de-serialisation techniques may be utilized by nodes of a blockchain network.

Unsorted sparse dictionary encodings are transformed into unsorted-dense or sorted-dense dictionary encodings. Sparse domain codes have large gaps between codes that are adjacent in order. Unlike spare codes, dense codes have smaller gaps between adjacent codes; consecutive codes are dense codes that have no gaps between adjacent codes. The techniques described herein are relational approaches that may be used to generate sparse composite codes and sorted codes.

Herein are fine grained updates to pieces of JavaScript object notation (JSON) documents by database statements that can update, delete, and insert parts of JSON documents. In an embodiment, a computer receives a request that specifies a modification of a JSON document that is stored in a compressed format in persistent storage. The modification adds additional content to the JSON document, and/or replaces an old value in the JSON document with a new value that is not a same size as the old value. The modification is recorded in a change log. The change log is eventually applied to the compressed format of the JSON document in the persistent storage without entirely rewriting the compressed format of the JSON document in the persistent storage.

An information processing device obtains an increasing tendency of a storage capacity utilized by a blog containing at least one article, sets, to the blog, a threshold for determining whether or not to compress at least a part of the article contained in the blog in accordance with the increasing tendency, determines whether or not the blog is to be compressed based on a total data amount of the at least one article contained in the blog and on the threshold, and determines whether or not to compress each of the at least one article contained in the blog in accordance with a degree of accessibility.

A method and system including receiving a main input stream for a compressed file at an application server, wherein the main input stream includes two or more file streams; extracting a file-type extension from each file stream input stream; determining the file-type extension is supported; determining, for each file stream with the supported file-type extension, a signature for the file stream with the supported file-type extension is valid; determining, for each valid file stream, a size of the file is less than a threshold level; and storing the valid file stream on a storage device when the size of the file is less than the threshold level. Numerous other aspects are provided.