The cache must remove/evict writers after a few seconds, but EhCache
only evicts entries when a new entry is added. That is not acceptable
for us, because that would leave lots of files open and we would need
a second mechanism to close them.
Therefore I write a simple wrapper for a ConcurrentHashMap that evicts
entries after timeToLive+5s.
- PdbFiles no longer require dates to be monotonically
increasing. Therefore TagsToFile does not have to ensure
this. => We only have one file per Tags.
- Use EhCache instead of HashMap.
We now support negative values. This will allow us to
store time/value sequences that are not monotonically
increasing, so that we do not have to create multiple
files just because some values were send out of order.
This is done by first transforming the values into
positive values by using interleaved encoding (there
is a name for it, but I don't remember it). We are
mapping values like this:
0 -> 1
1 -> 2
-1 -> 3
2 -> 4
-2 -> 5
...
Renamed LongSequenceEncoderDecoder to VariableByteEncoder.
Made methods static.
when matching property values to the query. This is important when
you have a property value that is a prefix of another property value,
e.g., AuditService.logEvent and AuditService.logEvents.
- The DiskStorage uses only one file instead of millions.
Also the block size is only 512 byte instead of 4kb, which
helps to reduce the memory usage for short sequences.
- Update primitiveCollections to get the new LongList.range
and LongList.rangeClosed methods.
- BSFile now stores Time&Value sequences and knows how to
encode the time values with delta encoding.
- Doc had to do some magic tricks to save memory. The path
was initialized lazy and stored as byte array. This is no
longer necessary. The patch was replaced by the
rootBlockNumber of the BSFile.
- Had to temporarily disable the 'in' queries.
- The stored values are now processed as stream of LongLists
instead of Entry. The overhead for creating Entries is
gone, so is the memory overhead, because Entry was an
object and had a reference to the tags, which is
unnecessary.
It can store multiple streams of integers in a single
file. It uses blocks of 512 byte, which is only 1/8th
of the block size the file based data-store uses. This
reduces the overhead and waste of memory for short
integer streams significantly. Storing data in one big
file, instead of many small files, makes backups much
more efficient.
The new datetimepicker can be used to specify date ranges. We no longer
need to define a start date and a range. This simplifies the code
for zooming and shifting considerably.
ParallelRequestsAggregator generates a line plot that shows the number
of parallel requests among the plotted events.
This plot has two issues:
1. It only considers events that are plotted. Events that occur later,
but were started within the plotted time frame are not considered.
2. For performance reasons we are only plotting points when a value
changed. This leads to diagonal lines.
