Vineyard: Zero-Copy In-Memory Data Sharing for Big Data and ML
Shriira Press
How Vineyard shares dataframes, tensors, and graphs between systems with zero copies and no serialization.
Welcome to Vineyard: Zero-Copy In-Memory Data Sharing for Big Data and ML.
Vineyard, known by its shorter name v6d, is a cloud-native, in-memory, immutable data manager built to solve a quietly expensive problem: every time one stage of a data pipeline hands a dataframe, tensor, or graph to the next, the data is usually serialized, written somewhere, and read back again. Vineyard removes that cost by holding objects in shared memory and letting co-located processes read them through zero-copy memory mapping, no matter which engine or language produced them. This book walks from the problem to the design and out into production. We begin with why pipelines bleed time on serialization, then study Vineyard's metadata-payload object model, the vineyardd daemon and its shared-memory store, the IPC and RPC clients, the builder and resolver registry that teaches Vineyard about your data types, distributed and global objects across a cluster, and finally the Kubernetes operator and data-aware scheduler that make Vineyard a first-class cloud-native citizen. A closing chapter looks at real integrations and operational practice.
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We hope it serves you well.
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