Amazon Technologies, Inc.

Atilim Cetin

Timothy Andrew Rath

Sandeep Bhatia

Mustafa Ozan Ozen

Gaurav Gupta

Gaurav Saxena

Lonnie J Princehouse

Dumanshu Goyal

Nirmesh Khandelwal

Eric Coll

Nilesh Shahdadpuri

Methods, systems, and computer-readable media for partition splitting in a distributed database are disclosed. A partition of data is split into a first sub-partition and a second sub-partition. A first portion of the data is assigned to the first sub-partition, and a second portion of the data is assigned to the second sub-partition. One or more elements of the first portion of the data from the partition and an additional one or more elements of the first portion of the data from the first sub-partition are stored into a first node. One or more elements of the second portion of the data from the partition and an additional one or more elements of the second portion of the data from the second sub-partition are stored into a second node. The partition is prevented from receiving new data after the partition is split into the first and second sub-partitions.

Partition splitting in a distributed database

Techniques are described for clustering data at the point of ingestion for storage using scalable storage resources. To cluster data at the point of ingestion, a data ingestion and query service uses a multilevel hash tree (MLHT)-based index to map a hierarchy of attribute values associated with each data element onto a point of a MLHT (which itself conceptually maps onto a continuous range of values). The total range of the MLHT is divided into one or more data partitions, each of which is mapped to one or more physical storage resources. A mapping algorithm uses the hierarchy of attribute fields to calculate the position of each data element ingested and, consequently, a physical storage resource at which to store the data element.

Dynamic distributed data clustering using multi-level hash trees

A data storage and retrieval system receives data points for a time series. The data storage and retrieval system stores the data points for a first portion of the time series using a first data format. Based at least in part on an analysis of queries performed on the first portion of the time series, the data storage and retrieval system determines to store a second portion of the time series using a second data format. The data storage and retrieval system stores subsequently received data points of the time series in the second data format.

Dynamic data layouts for time-series data

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Vancouver, Canada

Atilim Cetin