Amazon Technologies, Inc.

Ramakrishna Kotla

Anurag Windlass Gupta

Andrew Edward Caldwell

Bhaven Avalani

Michail Petropoulos

John Benjamin Tobler

Stavros Harizopoulos

Andi Gutmans

Ankit Kumar Jain

Min Zhou

Ankit Malpani

Eli R Fisher

Systems and techniques are described herein for tiered storage of customer data accessed by a search service of a computing resource service provider. In some aspects, customer data may be received by a search instance executed across a plurality of compute nodes and provisioned by a search service. The customer data may be indexed and the data and resulting index may be stored locally by a first pool of hot compute nodes of the search instance. The customer data and index may be migrated and stored remotely by a data storage service. Metadata associated with the customer data and/or index may be stored in a second pool of warm compute nodes of the search instance. The warm compute nodes, upon receiving a request to access the customer data, may identify a location of the customer data and retrieve the customer data from the data storage service according to the metadata.

Warm tier storage for search service

A tree-based format may be implemented for data stored in a data store. A table may be maintained across one or multiple storage nodes in storage slabs. Storage slabs may be mapped to different nodes of a tree. Each node of the tree may be assigned a different range of distribution scheme values which identify what portions of the table are stored in the storage slab. Storage slabs mapped to child nodes in the tree may be assigned portions of the range of distribution scheme values assigned to a parent. Storage nodes may be added or removed for storing the table. Storage slabs may be moved from one storage node to another in order to accommodate the addition or removal of storage nodes.

Tree-based format for data storage

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Cupertino, CA, United States of America

Ramakrishna Kotla