Talk a bit more about the results (index).
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%K CBOR
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%A C. Bormann
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%A P. Hoffman
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%T RFC 8949, Concise Binary Object Representation (CBOR)
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%D 2020
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%I Internet Engineering Task Force (IETF)
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@ -44,7 +44,7 @@ define legend {
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cy = cy - hdiff
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legend_line(cy,lstartx,lendx,tstartx,black,"Cached db and index")
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cy = cy - hdiff
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legend_line(cy,lstartx,lendx,tstartx,pink,"FIFO db and cached index")
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legend_line(cy,lstartx,lendx,tstartx,pink,"Common db, cached index")
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cy = cy - hdiff
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legend_line(cy,lstartx,lendx,tstartx,blue,"Uncached db, cached index")
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cy = cy - hdiff
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@ -943,14 +943,47 @@ The experiment starts with a database containing 1,000 cars and goes up to 250,0
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.so graphs/query_index.grap
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.ps \n[PS]
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.QP
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This figure shows the request durations to retrieve data based on a basic index with a database containing up to 250k entries.
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This figure shows the request durations to retrieve data based on a basic index with a database containing up to 250k entries, both with linear and logarithmic scales.
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.QE
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Since there is only one value to retrieve, the request is quick and time is almost constant.
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When the value and the index are kept in memory (see \f[CW]RAM only\f[] and \f[CW]Cached db\f[]), the retrieval is almost instantaneous (about 50 to 120 ns).
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In case the value is on the disk, deserialization takes about 15 µs (see \f[CW]Uncached db, cached index\f[]).
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When the value and the index are kept in memory (see \f[CW]RAM only\f[], \f[CW]Cached db\f[] and \f[CW]Common db\f[]), the retrieval is almost instantaneous\*[*].
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.FOOTNOTE1
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About 110 to 120 ns for RAM-only and cached database.
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This is slightly more (about 200 ns) for Common database since there is a few more steps due to the inner structure to maintain.
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.FOOTNOTE2
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In case the value is on the disk, deserialization takes about 15 µs (see \f[CW]Uncached db\f[]).
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The request is a little longer when the index isn't cached (see \f[CW]Uncached db and index\f[]); in this case DODB walks the file-system to find the right symlink to follow, thus slowing the process even more, by up to 20%.
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The logarithmic scale version of this figure shows that RAM-only and Cached databases have exactly the same performance.
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The Common database is somewhat slower than these two due to the caching policy: when a value is asked, the Common database puts its key at the start of a list to represent a
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.I recent
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use of this data (respectively, the last values in this list are the least recently used entries).
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Thus, Common database takes 80 ns for its caching policy, which makes this database about 67% slower than the previous ones to retrieve a value.
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Uncached databases are far away from these results, as shown by the logarithmically scaled figure.
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The data cache improves the duration of the requests, this makes them at least a hundred times faster.
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The results depend on the data size; the bigger the data, the slower the serialization (and deserialization).
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That is why alternative encodings, such as CBOR,
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.[
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CBOR
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.]
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should be considered for large databases.
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.SS Partitions (1 to n relations)
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.LP
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.ps -2
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.so graphs/query_partition.grap
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.ps \n[PS]
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.SS Tags (n to n relations)
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.LP
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.ps -2
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.so graphs/query_tag.grap
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.ps \n[PS]
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.
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.SS Summary
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.ps -2
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.TS
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allbox tab(:);
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@ -965,31 +998,25 @@ Cached db and index:T{
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Performance for retrieving a value is the same as RAM only while
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enabling the admin to manually search for data on-disk.
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T}:about the same perfs
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Uncached db, cached index::300 to 400x slower
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Common db, cached index:T{
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Performance is still excellent while requiring a
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.UL configurable
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amount of RAM.
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Should be used by default.
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T}:T{
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67% slower (about 200 ns) which still is great
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T}
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Uncached db, cached index:Very slow. Common database should be considered instead.:170 to 180x slower
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Uncached db and index:T{
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Best memory footprint, worst performance.
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T}:400 to 500x slower
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T}:200 to 210x slower
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.TE
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.ps \n[PS]
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.B Conclusion :
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as expected, retrieving a single value is fast and the size of the database doesn't matter much.
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.SS Conclusion on performance
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As expected, retrieving a single value is fast and the size of the database doesn't matter much.
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Each deserialization and, more importantly, each disk access is a pain point.
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Caching the value enables a massive performance gain, data can be retrieved several hundred times quicker.
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.SS Partitions (1 to n relations)
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.LP
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.ps -2
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.so graphs/query_partition.grap
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.ps \n[PS]
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.SS Tags (n to n relations)
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.LP
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.ps -2
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.so graphs/query_tag.grap
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.ps \n[PS]
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.
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.
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.
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.SECTION Future work
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This section presents all the features I want to see in a future version of the DODB library.
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