Method and system are provided for writing output from map-reduce jobs to an archive file. The method may include providing an archive manager and exposing an interface to be called from map-reduce jobs to output to an archive file in a map-reduce distributed file system. The method may also include using a buffering database as a temporary cache to buffer updates to the archive file. Handling by the archive manager calls from map-reduce jobs may allow: reading directly from an archive file or from a job index at the buffering database; writing to a job index at the buffering database used as a temporary cache to buffer updates; and serializing updates from the buffering database to the archive file.

Techniques for using erasure coding in a single region to reduce the likelihood of losing objects in a cloud object storage platform are provided. In one set of embodiments, a computer system can upload a plurality of data objects to a region of a cloud object storage platform, where the plurality of data objects including modifications to a data set. The computer system can further compute a parity object based on the plurality of data objects, where the parity object encodes parity information for the plurality of data objects. The computer system can then upload the parity object to the same region where the plurality of data objects was uploaded.

The present disclosure describes transaction-enabling systems and methods. A system can include a facility including a core task including a customer relevant output and a controller. The controller may include a facility description circuit to interpret a plurality of historical facility parameter values and corresponding facility outcome values and a facility prediction circuit to operate an adaptive learning system, wherein the adaptive learning system is configured to train a facility production predictor in response to the historical facility parameter values and the corresponding outcome values. The facility description circuit also interprets a plurality of present state facility parameter values, wherein the trained facility production predictor determines a customer contact indicator in response to the plurality of present state facility parameter values and a customer notification circuit provides a notification to a customer in response.

A shared-nothing database system is provided in which parallelism and workload balancing are increased by assigning the rows of each table to “slices”, and storing multiple copies (“duplicas”) of each slice across the persistent storage of multiple nodes of the shared-nothing database system. When the data for a table is distributed among the nodes of a shared-nothing system in this manner, requests to read data from a particular row of the table may be handled by any node that stores a duplica of the slice to which the row is assigned. For each slice, a single duplica of the slice is designated as the “primary duplica”. All DML operations (e.g. inserts, deletes, updates, etc.) that target a particular row of the table are performed by the node that has the primary duplica of the slice to which the particular row is assigned. The changes made by the DML operations are then propagated from the primary duplica to the other duplicas (“secondary duplicas”) of the same slice.

The subject technology determines, using a connection to an external data source, a set of shards stored in an external data source, the connection to the external data source being established using an external integration, the external integration including security and configuration information. The subject technology determines a set of offsets of each shard of the set of shards. The subject technology generates a query plan indicating a degree of parallelism based at least in part on a size of the set of offsets. The subject technology, based on the set of shards and the set of offsets, performs an operation on the external data source by performing, using the connection to the external data source, a write operation from a query statement on the external data source, the external data source being different than a storage platform associated with the system.

This disclosure provides for improvements in managing multi-drive, multi-die or multi-plane NAND flash memory. In one embodiment, the host directly assigns physical addresses and performs logical-to-physical address translation in a manner that reduces or eliminates the need for a memory controller to handle these functions, and initiates functions such as wear leveling in a manner that avoids competition with host data accesses. A memory controller optionally educates the host on array composition, capabilities and addressing restrictions. Host software can therefore interleave write and read requests across dies in a manner unencumbered by memory controller address translation. For multi-plane designs, the host writes related data in a manner consistent with multi-plane device addressing limitations. The host is therefore able to “plan ahead” in a manner supporting host issuance of true multi-plane read commands.

A wireless communication network serves a wireless user device with a wireless communication service from a wireless network slice that includes a Virtual Network Function (VNF). The VNF maintains hardware-trust with a distributed ledger. The distributed ledger maintains hardware-trust with the VNF. The VNF delivers the wireless communication service to the wireless user device from the wireless network slice. The VNF generates slice data that characterizes the service delivery. When the VNF maintains the hardware-trust with the distributed ledger, the VNF transfers the slice data to the distributed ledger. When the distributed ledger maintains the hardware-trust with the VNF, the distributed ledger stores the slice data.

Embodiments of the present disclosure provide a hybrid approach to performing a lazy pull of a container image. A file system in user space (FUSE) is utilized to lazy pull the container image, and manage file requests from the container while the container image is being fetched locally. During the retrieving, the FUSE may receive from the container, one or more file requests, and may temporarily block each of the one or more file requests until it can process them. Once the container image is fully fetched locally, the overlay structure of the container image expected by a file system in the kernel (e.g., Overlay FS) is created and control is passed to the file system in the kernel. The FUSE may then unmount itself, to expose the container to the underlying mount point.

A method, an apparatus, and an electronic device for processing a data transaction are disclosed. The method includes receiving an application request from a client to perform a data operation in a target data partition; creating a corresponding data transaction according to the application request, and assigning a transaction identifier to the data transaction; returning the transaction identifier that is assigned to the data transaction to the client; performing the data operation based on the target data partition according to the data operation carrying the transaction identifier and sent by the client; and processing the data transaction according to a transaction instruction sent by the client. The method enables a data operation to implement transactional attributes, and to satisfy a transactional nature of the data operation. Moreover, the service logic of data transactions implemented by the method is relatively simple, thus ensuring that data services have a good transactional nature.

An example operation may include one or more of receiving a data block for storage on a blockchain from an orderer node, the data block comprising a full-step hash of a storage request and a reduced-step hash of the storage request, performing an approximate hash verification on the data block based on the reduced-step hash of the storage request included in the data block, and in response to a success of the approximate hash verification, committing the data block among a hash-linked chain of data blocks stored within a distributed ledger of a blockchain.