The search bar is one of the means of finding data in Datahub. In this document, we discuss more effective ways of finding information beyond doing a standard keyword search. This is because keyword searches can return results from almost any part of an entity.
Dataset Properties are indexed in ElasticSearch the manner of key=value. Hence if you know the precise key-value pair, you can search using ```key=value```. However, if you only know the key, you can use wildcards to replace the value and that is what is being done here.
3.*Find a dataset with a column name, **latitude***
fieldPaths is the name of the attribute that holds the column name in Datasets.
4.*Find a dataset with the term **latitude** in the field description*
```editedFieldDescriptions: latitude OR fieldDescriptions: latitude``` [Sample results](https://demo.datahubproject.io/search?page=1&query=editedFieldDescriptions%3A%20latitude%20OR%20fieldDescriptions%3A%20latitude)
Datasets has 2 attributes that contains field description. fieldDescription comes from the SchemaMetadata aspect, while editedFieldDescriptions comes from the EditableSchemaMetadata aspect. EditableSchemaMetadata holds information that comes from UI edits, while SchemaMetadata holds data from ingestion of the dataset.
5.*Find a dataset with the term **logical** in the dataset description*
```editedDescription: *logical* OR description: *logical*``` [Sample results](https://demo.datahubproject.io/search?page=1&query=editedDescription%3A%20%2Alogical%2A%20OR%20description%3A%20%2Alogical%2A)
Similar to field descriptions, dataset descriptions can be found in 2 aspects, hence the need to search 2 attributes.
6.*Find a dataset which reside in one of the browsing folders, for instance, the **hive** folder*
BrowsePath is stored as a complete string, for instance ```/datasets/prod/hive/SampleKafkaDataset```, hence the need for wildcards on both ends of the term to return a result.
## Where to find more information?
The sample queries here are non exhaustive. [The link here](https://demo.datahubproject.io/tag/urn:li:tag:Searchable) shows the current list of indexed fields for each entity inside Datahub. Click on the fields inside each entity and see which field has the tag ```Searchable```.
However, it does not tell you the specific attribute name to use for specialized searches. One way to do so is to inspect the ElasticSearch indices, for example:
```curl http://localhost:9200/_cat/indices``` returns all the ES indices in the ElasticSearch container.
```
yellow open chartindex_v2_1643510690325 bQO_RSiCSUiKJYsmJClsew 1 1 2 0 8.5kb 8.5kb
yellow open mlmodelgroupindex_v2_1643510678529 OjIy0wb7RyKqLz3uTENRHQ 1 1 0 0 208b 208b
yellow open dataprocessindex_v2_1643510676831 2w-IHpuiTUCs6e6gumpYHA 1 1 0 0 208b 208b
yellow open corpgroupindex_v2_1643510673894 O7myCFlqQWKNtgsldzBS6g 1 1 3 0 16.8kb 16.8kb
yellow open corpuserindex_v2_1643510672335 0rIe_uIQTjme5Wy61MFbaw 1 1 6 2 32.4kb 32.4kb
yellow open datasetindex_v2_1643510688970 bjBfUEswSoSqPi3BP4iqjw 1 1 15 0 29.2kb 29.2kb
yellow open dataflowindex_v2_1643510681607 N8CMlRFvQ42rnYMVDaQJ2g 1 1 1 0 10.2kb 10.2kb
yellow open dataset_datasetusagestatisticsaspect_v1_1643510694706 kdqvqMYLRWq1oZt1pcAsXQ 1 1 4 0 8.9kb 8.9kb
yellow open .ds-datahub_usage_event-000003 YMVcU8sHTFilUwyI4CWJJg 1 1 186 0 203.9kb 203.9kb
yellow open datajob_datahubingestioncheckpointaspect_v1 nTXJf7C1Q3GoaIJ71gONxw 1 1 0 0 208b 208b
yellow open .ds-datahub_usage_event-000004 XRFwisRPSJuSr6UVmmsCsg 1 1 196 0 165.5kb 165.5kb
yellow open .ds-datahub_usage_event-000005 d0O6l5wIRLOyG6iIfAISGw 1 1 77 0 108.1kb 108.1kb
yellow open dataplatformindex_v2_1643510671426 _4SIIhfAT8yq_WROufunXA 1 1 0 0 208b 208b
yellow open mlmodeldeploymentindex_v2_1643510670629 n81eJIypSp2Qx-fpjZHgRw 1 1 0 0 208b 208b
