From 967de04257fb57459e21625de65e81d66705fc2e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Christoph=20B=C3=BCscher?= Date: Thu, 24 Jan 2019 22:54:55 +0100 Subject: [PATCH] Uppercasing some docs section title (#37781) Section titles are mostly uppercase, only a few cases where query DSL parameters or Java method names are used as the title they should be lowercased. --- docs/community-clients/index.asciidoc | 2 +- .../bucket/significantterms-aggregation.asciidoc | 6 +++--- docs/reference/migration/migrate_7_0/mappings.asciidoc | 4 ++-- docs/reference/testing/testing-framework.asciidoc | 4 ++-- 4 files changed, 8 insertions(+), 8 deletions(-) diff --git a/docs/community-clients/index.asciidoc b/docs/community-clients/index.asciidoc index 071eadb8bc5..58a6e625aa8 100644 --- a/docs/community-clients/index.asciidoc +++ b/docs/community-clients/index.asciidoc @@ -131,7 +131,7 @@ The following project appears to be abandoned: Node.js client for the Elasticsearch REST API [[kotlin]] -== kotlin +== Kotlin * https://github.com/mbuhot/eskotlin[ES Kotlin]: Elasticsearch Query DSL for kotlin based on the {client}/java-api/current/index.html[official Elasticsearch Java client]. diff --git a/docs/reference/aggregations/bucket/significantterms-aggregation.asciidoc b/docs/reference/aggregations/bucket/significantterms-aggregation.asciidoc index 1c615e795c6..e29fbac0c56 100644 --- a/docs/reference/aggregations/bucket/significantterms-aggregation.asciidoc +++ b/docs/reference/aggregations/bucket/significantterms-aggregation.asciidoc @@ -337,7 +337,7 @@ The JLH score can be used as a significance score by adding the parameter The scores are derived from the doc frequencies in _foreground_ and _background_ sets. The _absolute_ change in popularity (foregroundPercent - backgroundPercent) would favor common terms whereas the _relative_ change in popularity (foregroundPercent/ backgroundPercent) would favor rare terms. Rare vs common is essentially a precision vs recall balance and so the absolute and relative changes are multiplied to provide a sweet spot between precision and recall. -===== mutual information +===== Mutual information Mutual information as described in "Information Retrieval", Manning et al., Chapter 13.5.1 can be used as significance score by adding the parameter [source,js] @@ -373,7 +373,7 @@ Chi square as described in "Information Retrieval", Manning et al., Chapter 13.5 Chi square behaves like mutual information and can be configured with the same parameters `include_negatives` and `background_is_superset`. -===== google normalized distance +===== Google normalized distance Google normalized distance as described in "The Google Similarity Distance", Cilibrasi and Vitanyi, 2007 (http://arxiv.org/pdf/cs/0412098v3.pdf) can be used as significance score by adding the parameter [source,js] @@ -412,7 +412,7 @@ It is hard to say which one of the different heuristics will be the best choice If none of the above measures suits your usecase than another option is to implement a custom significance measure: -===== scripted +===== Scripted Customized scores can be implemented via a script: [source,js] diff --git a/docs/reference/migration/migrate_7_0/mappings.asciidoc b/docs/reference/migration/migrate_7_0/mappings.asciidoc index e4d38d9a643..653dd2fb4ca 100644 --- a/docs/reference/migration/migrate_7_0/mappings.asciidoc +++ b/docs/reference/migration/migrate_7_0/mappings.asciidoc @@ -67,8 +67,8 @@ should also be changed in the template to explicitly define `tree` to one of `ge or `quadtree`. This will ensure compatibility with previously created indexes. [float] -==== deprecated `geo_shape` parameters +==== Deprecated `geo_shape` parameters The following type parameters are deprecated for the `geo_shape` field type: `tree`, `precision`, `tree_levels`, `distance_error_pct`, `points_only`, and `strategy`. They -will be removed in a future version. \ No newline at end of file +will be removed in a future version. diff --git a/docs/reference/testing/testing-framework.asciidoc b/docs/reference/testing/testing-framework.asciidoc index 321122d81f5..9603ac6c703 100644 --- a/docs/reference/testing/testing-framework.asciidoc +++ b/docs/reference/testing/testing-framework.asciidoc @@ -8,7 +8,7 @@ Testing is a crucial part of your application, and as information retrieval itse [[why-randomized-testing]] -=== why randomized testing? +=== Why randomized testing? The key concept of randomized testing is not to use the same input values for every testcase, but still be able to reproduce it in case of a failure. This allows to test with vastly different input variables in order to make sure, that your implementation is actually independent from your provided test data. @@ -48,7 +48,7 @@ We provide a few classes that you can inherit from in your own test classes whic [[unit-tests]] -=== unit tests +=== Unit tests If your test is a well isolated unit test which doesn't need a running Elasticsearch cluster, you can use the `ESTestCase`. If you are testing lucene features, use `ESTestCase` and if you are testing concrete token streams, use the `ESTokenStreamTestCase` class. Those specific classes execute additional checks which ensure that no resources leaks are happening, after the test has run.