Java client issues batch 3

[l-trotta]

Fixes provided in this PR:

• 456: policy name in ILM should be optional. docs
• 457: VariableWidthHistogramAggregation missing the script field. server code class, which extends this class, which has script.
• 460: applies fix from this comment. @Anaethelion @flobernd in the java client generator I had to replace {dynamic_property} with {dynamic_type}, so there's a possibility that it could affect other client generators.
• 466,766: bucket aggregation subclasses should not have name or meta fields.
• 472: primaryTerm in IndexResponse should be optional. no hard evidence from server, but running an indexing request with a noop pipeline (check the issue) effectively returns a response with no primaryTerm.
• 506: added LearningToRankRescorer (from plugins) to Rescorer. server code + builder
• 528: escaped_tags was missing from HtmlStripCharFilter. docs, server code
• 533: per_field_analyzer in MoreLikeThisQuery should only be inside like and not a level above. server code where it's parsed at the same level as the other "like options".
• 551: added composite as a RuntimeFieldType. docs
• 555: min and max in ExtendedBounds should be optional. server code
• 572: added body to IndicesSimulateIndexTemplateResponse, made IndicesSimulateIndexTemplateRequest.ts and IndicesSimulateTemplateRequest.ts consistent with the server code.
  • SimulateIndexTemplateAction
  • SimulateTemplateAction -> transport -> body

[flobernd]

LGTM! Good improvements 🙂

[Anaethelion]

LGTM!

[github-actions]

Following you can find the validation results for the APIs you have changed.

API	Status	Request	Response
ilm.put_lifecycle	🔴	5/6	5/6
indices.simulate_index_template	🔴	5/7	4/7
indices.simulate_template	🔴	4/5	3/5
ml.clear_trained_model_deployment_cache	🔴	0/1	0/1
ml.close_job	🔴	63/64	62/63
ml.delete_calendar_event	🔴	3/4	3/4
ml.delete_calendar_job	🔴	2/3	2/3
ml.delete_calendar	🔴	4/5	4/5
ml.delete_data_frame_analytics	🔴	1/2	1/2
ml.delete_datafeed	🔴	2/3	2/3
ml.delete_expired_data	🔴	4/5	4/5
ml.delete_filter	🔴	26/27	26/27
ml.delete_forecast	🔴	2/3	2/3
ml.delete_job	🔴	46/47	46/47
ml.delete_model_snapshot	🔴	1/2	1/2
ml.delete_trained_model_alias	🔴	2/3	2/3
ml.delete_trained_model	🔴	3/4	3/4
ml.estimate_model_memory	🔴	15/16	15/16
ml.evaluate_data_frame	🔴	14/15	14/15
ml.explain_data_frame_analytics	🔴	6/7	6/7
ml.flush_job	🔴	14/15	14/15
ml.forecast	🔴	0/1	0/1
ml.get_buckets	🔴	13/14	13/14
ml.get_calendar_events	🔴	16/17	16/17
ml.get_calendars	🔴	16/17	16/17
ml.get_categories	🔴	11/12	11/12
ml.get_data_frame_analytics_stats	🔴	11/12	11/12
ml.get_data_frame_analytics	🔴	16/17	13/17
ml.get_datafeed_stats	🔴	26/27	26/27
ml.get_datafeeds	🔴	19/20	8/20
ml.get_filters	🔴	12/13	12/13
ml.get_influencers	🔴	10/11	10/11
ml.get_job_stats	🔴	31/32	31/32
ml.get_jobs	🔴	30/31	21/31
ml.get_memory_stats	🔴	5/6	5/6
ml.get_model_snapshot_upgrade_stats	🔴	2/3	2/3
ml.get_model_snapshots	🔴	17/18	17/18
ml.get_overall_buckets	🔴	15/16	14/15
ml.get_records	🔴	7/8	7/8
ml.get_trained_models_stats	🔴	16/17	9/17
ml.get_trained_models	🔴	30/37	31/37
ml.infer_trained_model	🔴	9/10	5/10
ml.info	🔴	9/10	1/10
ml.open_job	🔴	82/83	82/83
ml.post_calendar_events	🔴	20/21	20/21
ml.post_data	🔴	8/11	13/18
ml.preview_data_frame_analytics	🔴	2/3	2/3
ml.preview_datafeed	🔴	9/17	16/17
ml.put_calendar_job	🔴	10/12	11/12
ml.put_calendar	🔴	134/135	134/135
ml.put_data_frame_analytics	🔴	31/33	31/33
ml.put_datafeed	🔴	65/71	52/71
ml.put_filter	🔴	26/27	26/27
ml.put_job	🔴	218/227	222/225
ml.put_trained_model_alias	🔴	11/12	11/12
ml.put_trained_model_definition_part	⚪	Missing test	Missing test
ml.put_trained_model_vocabulary	⚪	Missing test	Missing test
ml.put_trained_model	🔴	13/15	5/15
ml.reset_job	🔴	1/2	1/2
ml.revert_model_snapshot	🔴	1/2	1/2
ml.set_upgrade_mode	🔴	5/6	5/6
ml.start_data_frame_analytics	🔴	0/1	0/1
ml.start_datafeed	🔴	23/24	23/24
ml.start_trained_model_deployment	🔴	12/13	2/13
ml.stop_data_frame_analytics	🔴	4/5	4/5
ml.stop_datafeed	🔴	16/17	16/17
ml.stop_trained_model_deployment	🔴	9/10	9/10
ml.update_data_frame_analytics	🔴	1/2	1/2
ml.update_datafeed	🔴	6/7	1/7
ml.update_filter	🔴	2/3	2/3
ml.update_job	🔴	3/5	4/5
ml.update_model_snapshot	🔴	2/3	2/3
ml.update_trained_model_deployment	🟠	Missing type	Missing type
ml.upgrade_job_snapshot	🔴	2/3	2/3
ml.validate_detector	🔴	1/2	1/2
ml.validate	🔴	2/3	2/3
msearch	🔴	14/17	15/16
search	🔴	1278/1925	1859/1907

You can validate these APIs yourself by using the make validate target.