Database Reference
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Figure 3-4. In the hybrid design, rows can be stored as a single data structure (blob). Note that the
actual compressed data would likely be in a binary, compressed format. The compressed data are
shown here in JSON format for ease of understanding.
Data in the wide table format shown in Figure 3-3 can be progressively converted to the
compressed format (blob style) shown in Figure 3-4 as soon as it is known that little or no
new data is likely to arrive for that time series and time window. Commonly, once the time
window ends, new data will only arrive for a few more seconds, and the compression of the
data can begin. Since compressed and uncompressed data can coexist in the same row, if a
few samples arrive after the row is compressed, the row can simply be compressed again to
merge the blob and the late-arriving samples.
The conceptual data flow for this hybrid-style time series database system is shown in Fig-
ure 3-5 .
Converting older data to blob format in the background allows a substantial increase in the
rate at which the renderer depicted in Figure 3-5 can retrieve data for presentation. On a
4-node MapR cluster, for instance, 30 million data points can be retrieved, aggregated and
plotted in about 20 seconds when data is in the compressed form.
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