3 ms·

Mireo SpaceTime – an absurdly fast spatiotemporal database

36 points by BerislavLopac 7y ago

kindkid 7y ago
Very cool! I'm particularly interested in this section: > SpaceTime database is built on a unique, multidimensional data index that automatically adapts to mutable and possibly highly skewed data distribution (which is usually the case with data coming from moving objects). There is one single multi-columnar index which indexes all associated columns of records at once. There are no secondary indices! > The physical model intertwines index and record data – as a consequence, records that are logically close (based on id, position and timestamp) are at the same time also physically close. In turn, this maximizes the throughput of disk reads. > The main ideas for inventing SpaceTime index came from several inspiring scientific papers. It is similar to the kd-tree family of indices, but with two major improvements: first, the index tree in SpaceTime is built using the bottom-up approach (as opposed to the top-down kd-tree construction) and second, the process of index creation adapts to particular space-time distribution of data. Kd-trees work well on a large scale only with static datasets; our bottom-up approach overcomes this. Can you provide links to the scientific papers that were mentioned? Are there any plans to publish a more detailed description of SpaceTime's index data structure and algorithm?
- miljen 7y ago
  Hi, thanks for the interest! Yes, we are planning to publish more details about the novel index structure, so feel free to visit https://blog.mireo.hr/ https://blog.mireo.hr/ every 2 weeks. Very soon we will also launch a live demo with 200,000 vehicles, so you'll be able to try SpaceTime capabilities on your own :)
Nikola12 7y ago
Can you give some example of "MSQL" query?
- miljen 7y ago
  Of course. MSQL queries can be as simple as "select * from st.trips", but can also include geospatial functions that we implemented and that are not part of standard SQL: "select vid, sum(sphere_length(x[0], y[0], x[1], y[1])) as mileage from st.segments where ST_Intersects( ST_GeomFromText('POLYGON ((11955008 38520960,11995328 38530624,11998976 38531456,11955008 38520960))'), ST_Line(x[0], y[0], x[1], y[1]) ) and t[0] >= 1569888000 and t[1] < 1572566400 and vid >= 3200 and vid <= 3300 group by vid" Actually, a query very similar to the one listed above generates the report mileage-in-area mentioned in the blog.

36 points by BerislavLopac 7y ago

Very cool! I'm particularly interested in this section: > SpaceTime database is built on a unique, multidimensional data index that automatically adapts to mutable and possibly highly skewed data distribution (which is usually the case with data coming from moving objects). There is one single multi-columnar index which indexes all associated columns of records at once. There are no secondary indices! > The physical model intertwines index and record data – as a consequence, records that are logically close (based on id, position and timestamp) are at the same time also physically close. In turn, this maximizes the throughput of disk reads. > The main ideas for inventing SpaceTime index came from several inspiring scientific papers. It is similar to the kd-tree family of indices, but with two major improvements: first, the index tree in SpaceTime is built using the bottom-up approach (as opposed to the top-down kd-tree construction) and second, the process of index creation adapts to particular space-time distribution of data. Kd-trees work well on a large scale only with static datasets; our bottom-up approach overcomes this. Can you provide links to the scientific papers that were mentioned? Are there any plans to publish a more detailed description of SpaceTime's index data structure and algorithm?

miljen 7y ago
Hi, thanks for the interest! Yes, we are planning to publish more details about the novel index structure, so feel free to visit https://blog.mireo.hr/ https://blog.mireo.hr/ every 2 weeks. Very soon we will also launch a live demo with 200,000 vehicles, so you'll be able to try SpaceTime capabilities on your own :)

Nikola12 7y ago

Can you give some example of "MSQL" query?

miljen 7y ago
Of course. MSQL queries can be as simple as "select * from st.trips", but can also include geospatial functions that we implemented and that are not part of standard SQL: "select vid, sum(sphere_length(x[0], y[0], x[1], y[1])) as mileage from st.segments where ST_Intersects( ST_GeomFromText('POLYGON ((11955008 38520960,11995328 38530624,11998976 38531456,11955008 38520960))'), ST_Line(x[0], y[0], x[1], y[1]) ) and t[0] >= 1569888000 and t[1] < 1572566400 and vid >= 3200 and vid <= 3300 group by vid" Actually, a query very similar to the one listed above generates the report mileage-in-area mentioned in the blog.