* [DOCS] Lens features and changes for 7.14 * Aggregation reference * Formatting * Fixes terminology * Updates from 8-Jul meeting * Terminology * Updates terminology, images, and tutorial steps * Update docs/user/dashboard/lens-advanced.asciidoc Co-authored-by: Wylie Conlon <wylieconlon@gmail.com> * Update docs/user/dashboard/create-panels-with-editors.asciidoc Co-authored-by: Wylie Conlon <wylieconlon@gmail.com> * Update docs/user/dashboard/lens.asciidoc Co-authored-by: Wylie Conlon <wylieconlon@gmail.com> * Comments from review * Cleans up unused images * Fixes image reference Co-authored-by: Wylie Conlon <wylieconlon@gmail.com>
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302 lines
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[[discover]]
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= Discover
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[partintro]
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--
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**_Gain insight to your data._**
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*Discover* enables you to quickly search and filter your data, get information
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about the structure of the fields, and visualize your data with *Lens* and *Maps*.
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You can customize and save your searches and place them on a dashboard.
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++++
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<script type="text/javascript" async src="https://play.vidyard.com/embed/v4.js">
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</script>
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<img
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style="width: 100%; margin: auto; display: block;"
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class="vidyard-player-embed"
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src="https://play.vidyard.com/c2qBPz74BU16ncbvDWGvbz.jpg"
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data-uuid="c2qBPz74BU16ncbvDWGvbz"
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data-v="4"
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data-type="inline"
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/>
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++++
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[float]
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=== Explore and query your data
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You have questions about your data.
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What pages on your website contain a
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specific word or phrase? What events were logged most recently?
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What processes take longer than 500 milliseconds to respond?
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This tutorial shows you how to use *Discover* to quickly search large amounts of
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data and understand what’s going on at any given time.
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You’ll learn to:
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- **Select** data for your exploration, set a time range for that data,
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search it with the {kib} Query Language, and filter the results.
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- **Explore** the details of your data, view individual documents, and create tables
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that summarize the contents of the data.
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- **Present** your findings in a visualization.
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At the end of this tutorial, you’ll be ready to start exploring with your own
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data in *Discover*.
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[float]
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=== Prerequisites
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- If you don’t already have {kib}, set it up with https://www.elastic.co/cloud/elasticsearch-service/signup?baymax=docs-body&elektra=docs[our free trial].
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- You must have data in {es}. This tutorial uses the
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<<gs-get-data-into-kibana,ecommerce sample data set>>, but you can use your own data.
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- You should have an understanding of {ref}/documents-indices.html[{es} documents and indices]
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and <<kibana-concepts-analysts, {kib} concepts>>.
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[float]
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[[find-the-data-you-want-to-use]]
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=== Find your data
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Tell {kib} where to find the data you want to explore, and then specify the time range in which to view that data.
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. Open the main menu, and select **Discover**.
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. Select the data you want to work with.
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+
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{kib} uses an <<index-patterns,index pattern>> to tell it where to find
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your {es} data.
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To view the ecommerce sample data, make sure the index pattern is set to **kibana_sample_data_ecommerce**.
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+
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[role="screenshot"]
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image::images/discover-index-pattern.png[How to set the index pattern in Discover, width=50%]
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. Adjust the <<set-time-filter,time range>> to view data for the *Last 7 days*.
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+
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The range selection is based on the default time field in your data.
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If you are using the sample data, this value was set when you added the data.
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If you are using your own data, and it does not have a time field, the range selection is not available.
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. To view the count of documents for a given time in the specified range,
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click and drag the mouse over the histogram.
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[float]
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[[explore-fields-in-your-data]]
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=== Explore the fields in your data
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**Discover** includes a table that shows all the documents that match your search.
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By default, the table includes columns for the time field and the document `_source`,
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which can be overwhelming. You’ll modify this table to display only your fields of interest.
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. Scan through the list of **Available fields** until you find the `manufacturer` field.
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You can also search for the field by name.
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+
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[role="screenshot"]
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image:images/discover-sidebar-available-fields.png[Fields list that displays the top five search results, width=50%]
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. Click the `manufacturer` field to view its five most popular values.
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+
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[role="screenshot"]
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image:images/find-manufacturer-field.png[Fields list that displays the top five search results, width=75%]
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. Click image:images/add-icon.png[Add icon] to toggle the field into the document table.
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. Find the `customer_first_name` and `customer_last_name` last name fields and add
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them to your document table. Your table should look similar to this:
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+
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[role="screenshot"]
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image:images/document-table.png[Document table with fields for manufacturer, customer_first_name, and customer_last_name]
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. To rearrange the table columns, hover the mouse over a
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column header, and then use the move controls.
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. To view more of the document table, click *Hide chart*.
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[float]
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[[add-field-in-discover]]
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=== Add a field to your index pattern
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What happens if you forgot to define an important value as a separate field? Or, what if you
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want to combine two fields and treat them as one? This is where {ref}/runtime.html[runtime fields] come into play.
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You can add a runtime field to your index pattern from inside of **Discover**,
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and then use that field for analysis and visualizations,
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the same way you do with other fields.
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. Click the ellipsis icon (...), and then click *Add field to index pattern*.
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+
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[role="screenshot"]
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image:images/add-field-to-pattern.png[Dropdown menu located next to index pattern field with item for adding a field to an index pattern, width=50%]
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. In the *Create field* form, enter `hello` for the name.
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. Turn on *Set value*.
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. Define the script using the Painless scripting language. Runtime fields require an `emit()`.
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+
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```ts
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emit("Hello World!");
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```
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. Click *Save*.
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. In the fields list, search for the *hello* field, and then add it to the table to view it's value.
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+
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[role="screenshot"]
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image:images/hello-field.png[hello field in the document table]
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. Create a second field named `customer` that combines customer last name and first initial.
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+
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```ts
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String str = doc['customer_first_name.keyword'].value;
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char ch1 = str.charAt(0);
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emit(doc['customer_last_name.keyword'].value + ", " + ch1);
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```
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. Simplify the the document table by removing `customer_first_name` and `customer_last_name` and adding `customer` in their place.
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+
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[role="screenshot"]
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image:images/customer.png[Customer last name, first initial in the document table]
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+
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For more information on adding fields and Painless scripting language examples,
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refer to <<runtime-fields, Explore your data with runtime fields>>.
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[float]
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[[search-in-discover]]
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=== Search your data
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One of the unique capabilities of **Discover** is the ability to combine
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free text search with filtering based on structured data.
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To search all fields, enter a simple string in the **Search** field.
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[role="screenshot"]
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image:images/discover-search-field.png[Search field in Discover]
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To search particular fields and
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build more complex queries, use the <<kuery-query,Kibana Query language>>.
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As you type, KQL prompts you with the fields you can search and the operators
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you can use to build a structured query.
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Search the ecommerce data for documents where the country matches US:
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. Enter `g`, and then select *geoip.country_iso_code*.
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. Select *equals some value* and *US*, and then click *Update*.
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. For a more complex search, try:
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+
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`geoip.country_iso_code : US and products.taxless_price >= 75`
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[float]
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[[filter-in-discover]]
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=== Filter your data
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Whereas the query defines the set of documents you are interested in,
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filters enable you to zero in on different subsets of those documents.
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You can filter results to include or exclude specific fields, filter for a value in a range,
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and more.
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Exclude documents where day of week is not Wednesday:
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. Click **Add filter**.
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. Set **Field** to *day_of_week*, **Operator** to *is not*, and **Value** to *Wednesday*.
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+
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[role="screenshot"]
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image:images/discover-add-filter.png[Add filter dialog in Discover]
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. Save the filter.
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. Continue your exploration by adding more filters.
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. To remove a filter,
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click the close icon (x) next to its name in the filter bar.
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[float]
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[[look-inside-a-document]]
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=== Look inside a document
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Dive into an individual document to view its fields and the documents
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that occurred before and after it.
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. In the document table, expand any document.
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+
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[role="screenshot"]
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image:images/document-table-expanded.png[Table view with document expanded]
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. Scan through the fields and their values. If you find a field of interest,
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hover over its name for filters and other controls.
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. To view documents that occurred before or after the event you are looking at, click
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<<discover-view-surrounding-documents, View surrounding documents>>.
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. For direct access to a particular document, click **<<discover-view-single-document,View single document>>**.
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+
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You can bookmark this document and share the link.
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[float]
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[[save-your-search]]
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=== Save your search for later use
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Save your search so you can repeat it later, generate a CSV report, or use it in visualizations, dashboards, and Canvas workpads.
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Saving a search saves the query text, filters,
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and current view of *Discover*—the columns selected in the document table, the sort order, and the index pattern.
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. In the toolbar, click **Save**.
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. Give your search a title, and then click **Save**.
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+
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[role="screenshot"]
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image:images/discover-save-saved-search.png[Save saved search in Discover, width=50%]
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[float]
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=== Visualize your findings
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If a field can be {ref}/search-aggregations.html[aggregated], you can quickly
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visualize it from **Discover**.
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. From the **Available fields** list, click `day_of_week`, and then click **Visualize**.
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+
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[role="screenshot"]
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image:images/discover-visualize.png[Discover sidebar field popover with visualize button, width=75%]
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+
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{kib} creates a visualization best suited for this field.
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. From the *Available fields* list, drag and drop `manufacturer.keyword` onto the workspace.
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+
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[role="screenshot"]
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image:images/discover-from-visualize.png[Visualization that opens from Discover based on your data]
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. Save your visualization for use on a dashboard.
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+
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For geo point fields (image:images/geoip-icon.png[Geo point field icon, width=20px]),
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if you click **Visualize**,
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your data appears in a map.
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+
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[role="screenshot"]
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image:images/discover-maps.png[Map containing documents]
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[float]
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[[share-your-findings]]
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=== Share your findings
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To share your findings with a larger audience, click *Share* in the toolbar. For detailed information about the sharing options, refer to <<reporting-getting-started,Reporting>>.
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[float]
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=== What’s next?
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* <<kuery-query, Learn more about the structure of a KQL query>>.
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* <<discover-search-for-relevance, Search for relevance>>.
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* <<reporting-getting-started, Present your findings in a report>>.
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* <<kibana-discover-settings, Configure Discover>> to better meet your needs.
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Go to **Advanced Settings** to configure the number of documents to show,
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the table columns that display by default, and more.
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--
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include::{kib-repo-dir}/discover/view-document.asciidoc[]
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include::{kib-repo-dir}/discover/search-for-relevance.asciidoc[]
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include::{kib-repo-dir}/discover/save-search.asciidoc[]
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include::{kib-repo-dir}/discover/search-sessions.asciidoc[]
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