  We present VStore, a data store for supporting fast, resource-efficient
analytics over large archival videos. VStore manages video ingestion, storage,
retrieval, and consumption. It controls video formats along the video data
path. It is challenged by i) the huge combinatorial space of video format
knobs; ii) the complex impacts of these knobs and their high profiling cost;
iii) optimizing for multiple resource types. It explores an idea called
backward derivation of configuration: in the opposite direction along the video
data path, VStore passes the video quantity and quality expected by analytics
backward to retrieval, to storage, and to ingestion. In this process, VStore
derives an optimal set of video formats, optimizing for different resources in
a progressive manner. VStore automatically derives large, complex
configurations consisting of more than one hundred knobs over tens of video
formats. In response to queries, VStore selects video formats catering to the
executed operators and the target accuracy. It streams video data from disks
through decoder to operators. It runs queries as fast as 362x of video
realtime.
