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site/content/3.12/about-arangodb/_index.md

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## What are Graphs?
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Graphs are information networks comprised of nodes and edges.
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Graphs are information networks composed of nodes and edges.
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![An arrow labeled as "Edge" pointing from one circle to another, both labeled "Node"](../../images/data-model-graph-relation-abstract-edge.png)
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site/content/3.12/aql/execution-and-performance/query-profiling.md

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For understanding the performance of specific queries, you can profile them to
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identify slow parts of query execution plans
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---
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ArangoDB allows to execute your query with special instrumentation code enabled.
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ArangoDB allows you to execute your query with special instrumentation code enabled.
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It provides you a query plan with detailed execution statistics.
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To use this in an interactive fashion on the shell you can use

site/content/3.12/aql/functions/date.md

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## Date and time representations
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AQL offers functionality to work with dates, but it does not have a special data type
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for dates (neither does JSON, which is usually used as format to ship data into and
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for dates (neither does JSON, which is usually used as a format to ship data into and
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out of ArangoDB). Instead, dates in AQL are represented by either numbers or strings.
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All date function operations are done in the *Unix time* system. Unix time counts
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all non leap seconds beginning with January 1st 1970 00:00:00.000 UTC, also know as
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the Unix epoch. A point in time is called timestamp. A timestamp has the same value
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all non leap seconds beginning with January 1st 1970 00:00:00.000 UTC, also known as
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the Unix epoch. A point in time is called a timestamp. A timestamp has the same value
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at every point on earth. The date functions use millisecond precision for timestamps.
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Time unit definitions:
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`DATE_ISO8601(year, month, day, hour, minute, second, millisecond) → dateString`
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Return a ISO 8601 date time string from `date`, but allows to specify the individual
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Return an ISO 8601 date time string from `date`, but allows you to specify the individual
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date components separately. All parameters after `day` are optional.
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- **year** (number): typically in the range 0..9999, e.g. `2017`
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`DATE_TIMESTAMP(year, month, day, hour, minute, second, millisecond) → timestamp`
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Create a timestamp value, but allows to specify the individual date components
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Create a timestamp value, but allows you to specify the individual date components
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separately. All parameters after `day` are optional.
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- **year** (number): typically in the range 0..9999, e.g. `2017`
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---
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name: datedysmn4
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description: |
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Determine the number of days in February in a a non-leap year using a date time string:
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Determine the number of days in February in a non-leap year using a date time string:
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---
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RETURN DATE_DAYS_IN_MONTH("2021-02-01")
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```

site/content/3.12/aql/functions/numeric.md

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`EXP(value) → num`
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Return Euler's constant (2.71828...) raised to the power of *value*.
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Return Euler's constant (2.71828...) raised to the power of the *value*.
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- **value** (number): the input value
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- returns **num** (number): Euler's constant raised to the power of *value*
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- returns **num** (number): Euler's constant raised to the power of the *value*
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```aql
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EXP(1) // 2.718281828459045
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`EXP2(value) → num`
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Return 2 raised to the power of *value*.
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Return 2 raised to the power of the *value*.
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- **value** (number): the input value
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- returns **num** (number): 2 raised to the power of *value*
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- returns **num** (number): 2 raised to the power of the *value*
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```aql
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EXP2(16) // 65536

site/content/3.12/aql/graphs/shortest-path.md

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```
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All collections in the list that do not specify their own direction use the
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direction defined after `IN` (here: `OUTBOUND`). This allows to use a different
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direction defined after `IN` (here: `OUTBOUND`). This allows you to use a different
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direction for each collection in your path search.
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## Conditional shortest path

site/content/3.12/aql/graphs/traversals.md

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```
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All collections in the list that do not specify their own direction use the
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direction defined after `IN`. This allows to use a different direction for each
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direction defined after `IN`. This allows you to use a different direction for each
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collection in your traversal.
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### Graph traversals in a cluster
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The depth at which a traversal is stopped by pruning is considered as a result,
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but in the above example, the minimum depth of `2` filters the start node out.
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If you lower the minimum depth to `0`, you get **London** as the sole result.
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This confirms that the traversal stopped at the start vertex.
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This confirms that the traversal stopped at the start node.
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To avoid this problem, exclude the `null` value. For example, you can use
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`e.travelTime > 0 AND e.travelTime < 2.5`, but more generic solutions are to

site/content/3.12/arangograph/my-account.md

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1. Hover over or click the user icon of the __User Toolbar__ in the top right corner.
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2. Click __My organizations__ in the __My account__ section.
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3. Click the __New organization__ button.
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4. Enter a name and and a description for the new organization and click the
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4. Enter a name and a description for the new organization and click the
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__Create__ button.
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{{< info >}}

site/content/3.12/components/tools/arangoimport/examples-json.md

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Using multiple threads may lead to a non-sequential import of the input
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data. Data that appears later in the input file may be imported earlier than data
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that appears earlier in the input file. This is normally not a problem but may cause
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issues when when there are data dependencies or duplicates in the import data. In
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issues when there are data dependencies or duplicates in the import data. In
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this case, the number of threads should be set to 1. Also, using parallelism with
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the `--threads X` parameter together with the `--on-duplicate` parameter set to `ignore`,
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`update` or `replace` can lead to a race condition, when there are duplicates e.g. multiple

site/content/3.12/concepts/data-models.md

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## Graph Model
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Graphs are comprised of **nodes** and **edges**. Both are documents in
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Graphs are composed of **nodes** and **edges**. Both are documents in
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ArangoDB. Edges have two special attributes, `_from` and `_to`, that reference
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the source and target nodes by their document identifiers.
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site/content/3.12/data-science/integrations/_index.md

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- adapters
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ArangoDB Adapters provide a convenient way to integrate ArangoDB with popular
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data science tools. By enabling you to to use your preferred programming
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data science tools. By enabling you to use your preferred programming
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languages and libraries, these adapters simplify the data analysis
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process and make it easier to leverage the power of ArangoDB in data science.
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