Elastic Stack 7.0.0 特性介绍
Kibana 7.0: new design & navigation … and dark mode!
A new era for cluster coordination in Elasticsearch
scale resilient 弹性
cluster coordination layer Zen Discovery
Zen2 is a completely new cluster coordination layer
faster, safer, and easier to use
there are well-known consensus algorithms, like Paxos, Raft, Zab and Viewstamped Replication (VR)
the demands of an Elasticsearch cluster require higher throughput for cluster changes,
support for easily growing or shrinking a cluster,
and a seamless rolling upgrade strategy to allow 6.7 clusters to do a rolling upgrade to 7.0,
features that these reference algorithms couldn’t provide.
高吞吐量集群变更 ， 集群 扩容 缩容 无缝滚动升级
Zen2 also includes a number of changes that reduce the likelihood of human error
and provides clearer choices when recovering from catastrophic failure.
It’s not easy to improve reliability, performance and user experience all at once, especially in such a central component.
more about Zen2
Individual nodes in Elasticsearch are built with resiliency in mind.
If you send too many requests to a node or your requests are too large, the node will push back.
断路器 circuit breakers
For nodes with smaller JVM heap sizes,
which are becoming more common as users move to a cluster-per-tenant model
rather than a massive multitenant cluster, this is even more important.
In 7.0, we’re introducing the real memory circuit breaker,
which much more accurately detects unserviceable requests,
and prevents them from making an individual node unstable.
Giving relevance and speed a boost across use cases
相关性 和 速度
Faster top k queries
In many search use cases, quickly seeing the top k (say 20) results on a query matters much more to the user than the exact hit count
S7.0(Lucene 8.0)实现了一种新的算法(Block-Max WAND)
legal and patent search, introduce the need to find records in which words or phrases are within a certain distance from each other.
法律和专利搜索 记录和词 短语的 距离匹配
Intervals queries in Elasticsearch 7.0 introduce a brand new way of structuring such queries,
and are significantly simpler to use and define compared to the previous method (span queries).
Intervals queries are also much more resilient to edge cases compared to span queries.
Function score 2.0
Custom scoring relevancy and results ranking
自定义打分 相关性 结果排序
7.0 introduces the next generation of function score capability
that provides a simpler, modular, and more flexible way to generate a ranking score per record.
The new modular structure allows users to mix
and match a set of arithmetic and distance functions to construct arbitrary function score calculations,
giving them more control over how results are scored and ranked.
Smooth zoom in Elastic Maps with geotile grid
introducing a new aggregation in Elasticsearch to handle (geo) map tiles in a way
that allows a user to zoom in and out on the map without any change to the shape of the result data.
The new geotile_grid aggregation groups geo_points into buckets that represent cells in a grid,
with each cell correlating with a tile in a map.
Prior to this change, the fringes of the shape could slightly change with the change in zoom level,
because the rectangular tiles would change orientation at different zoom levels.
Elastic Maps in 7.0 is already using this new aggregation to ensure that your view stays stable as you zoom in and out.
Strengthening time series use cases with nanosecond precision support
Whether it’s infrastructure metrics, system audit logs, network traffic, or a rover on Mars,
time series data is central to how many people use the Elastic Stack.
The ability to precisely order and correlate events across multiple systems and services is key.
Up until now, Elasticsearch only stored timestamps with millisecond precision.
7.0 adds a few zeroes and brings nanosecond precision,
which allows users with high-frequency data collection needs the precision
required to accurately store and sequence this data.
The change was made possible by migrating from the historical JODA library to the official Java time API in JDK 8.
不使用 select * 的七个理由