Currently we use 5k operations as a flush threshold. Indexing 5k documents
per second is rather common which would cause the index to be committed on
the lucene level each time the flush logic runs which is 5 seconds by default.
We should rather use a size based threshold similar to the lucene index writer
that doesn't cause such agressive commits which can slow down indexing significantly
especially since they cause the underlying devices to fsync their data.
Load tests showed that SerialMS has problems to keep up with
the merges under high load. We should switch back to CMS
until we have a better story to balance merge
threads / efforts across shards on a single node.
Closes#5817
Today, we use ConcurrentMergeScheduler, and this can be painful since it is concurrent on a shard level, with a max of 3 threads doing concurrent merges. If there are several shards being indexed, then there will be a minor explosion of threads trying to do merges, all being throttled by our merge throttling.
Moving to serial merge scheduler will still maintain concurrency of merges across shards, as we have the merge thread pool that schedules those merges. It will just be a serial one on a specific shard.
Also, on serial merge scheduler, we now have a limit of how many merges it will do at one go, so it will let other shards get their fair chance of merging. We use the pending merges on IW to check if merges are needed or not for it.
Note, that if a merge is happening, it will not block due to a sync on the maybeMerge call at indexing (flush) time, since we wrap our merge scheduler with the EnabledMergeScheduler, where maybeMerge is not activated during indexing, only with explicit calls to IW#maybeMerge (see Merges).
closes#5447
Removed unused misc.asciidoc file
Added plugins directory to directory layout
Fixed transport.tcp.connect_timeout value to match the code found in NetworkService.TcpSettings
Clarified that phrase query does not preserve order of terms
Clarified merge page
Added instructions on how to build documentation to docs/README
* Clean up s/ElasticSearch/Elasticsearch on docs/*
* Clean up s/ElasticSearch/Elasticsearch on src/* bin/* & pom.xml
* Clean up s/ElasticSearch/Elasticsearch on NOTICE.txt and README.textile
Closes#4634
This adds the field data circuit breaker, which is used to estimate
the amount of memory required to load field data before loading it. It
then raises a CircuitBreakingException if the limit is exceeded.
It is configured with two parameters:
`indices.fielddata.cache.breaker.limit` - the maximum number of bytes
of field data to be loaded before circuit breaking. Defaults to
`indices.fielddata.cache.size` if set, unbounded otherwise.
`indices.fielddata.cache.breaker.overhead` - a contast for all field
data estimations to be multiplied with before aggregation. Defaults to
1.03.
Both settings can be configured dynamically using the cluster update
settings API.
This commits add doc values support to geo point using the exact same approach
as for numeric data: geo points for a given document are stored uncompressed
and sequentially in a single binary doc values field.
Close#4207
This commit changes field data configuration updates so that they are
immediately taken into account for loading new segments. The way it works
is that field data configuration is now cached separately from the field
data cache, meaning that it is now possible to clear the field data
configuration from IndexFieldDataService while the cache will stay around. On
the next time that Elasticsearch will reload field data configuration, it will
check if there is already a cache entry, and reuse it if it exists.
To disable field data loading, all that is required is to change the field
data format to "none" (supported by all field data types) using the update
mapping API. Elasticsearch will then refuse to load field data on any new
segment, but field data which has been loaded on the previous segments will
remain available. So you need to clear the field data cache in order to
reclaim memory (otherwise memory will be reclaimed slower, as segments get
merged).
Close#4430Close#4431
This commit allows for using Lucene doc values as a backend for field data,
moving the cost of building field data from the refresh operation to indexing.
In addition, Lucene doc values can be stored on disk (partially, or even
entirely), so that memory management is done at the operating system level
(file-system cache) instead of the JVM, avoiding long pauses during major
collections due to large heaps.
So far doc values are supported on numeric types and non-analyzed strings
(index:no or index:not_analyzed). Under the hood, it uses SORTED_SET doc values
which is the only type to support multi-valued fields. Since the field data API
set is a bit wider than the doc values API set, some operations are not
supported:
- field data filtering: this will fail if doc values are enabled,
- field data cache clearing, even for memory-based doc values formats,
- getting the memory usage for a specific field,
- knowing whether a field is actually multi-valued.
This commit also allows for configuring doc-values formats on a per-field basis
similarly to postings formats. In particular the doc values format of the
_version field can be configured through its own field mapper (it used to be
handled in UidFieldMapper previously).
Closes#3806
* Merged segments are now warmed-up at the end of the merge operation instead
of _refresh, so that _refresh doesn't pay the price for the warm-up of merged
segments, which is often higher than flushed segments because of their size.
* Even when no _warmer is registered, some basic warm-up of the segments is
performed: norms, doc values (_version). This should help a bit people who
forget to register warmers.
* Eager loading support for the parent id cache and field data: when one
can't predict what terms will be present in the index, it is tempting to use
a match_all query in a warmer, but in that case, query execution might not be
much faster than field data loading so having a warmer that only loads field
data without running a query can be useful.
Closes#3819
This commit adds two main pieces, the first is a ClusterInfoService
that provides a service running on the master nodes that fetches the
total/free bytes for each data node in the cluster as well as the
sizes of all shards in the cluster. This information is gathered by
default every 30 seconds, and can be changed dynamically by setting
the `cluster.info.update.interval` setting. This ClusterInfoService
can hopefully be used in the future to weight nodes for allocation
based on their disk usage, if desired.
The second main piece is the DiskThresholdDecider, which can disallow
a shard from being allocated to a node, or from remaining on the node
depending on configuration parameters. There are three main
configuration parameters for the DiskThresholdDecider:
`cluster.routing.allocation.disk.threshold_enabled` controls whether
the decider is enabled. It defaults to false (disabled). Note that the
decider is also disabled for clusters with only a single data node.
`cluster.routing.allocation.disk.watermark.low` controls the low
watermark for disk usage. It defaults to 0.70, meaning ES will not
allocate new shards to nodes once they have more than 70% disk
used. It can also be set to an absolute byte value (like 500mb) to
prevent ES from allocating shards if less than the configured amount
of space is available.
`cluster.routing.allocation.disk.watermark.high` controls the high
watermark. It defaults to 0.85, meaning ES will attempt to relocate
shards to another node if the node disk usage rises above 85%. It can
also be set to an absolute byte value (similar to the low watermark)
to relocate shards once less than the configured amount of space is
available on the node.
Closes#3480
Simon Willnauer
Christoph Frick
Kouhei Sutou
Kevin Wang
Martijn van Groningen
Lee Hinman
Shay Banon
Konrad Feldmeier
Oleg Anashkin
Clinton Gormley
Brusic
Adrien Grand