key concepts restructure proposal

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Scott Anderson 2019-10-18 16:49:57 -06:00
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The InfluxDB v2 API provides a programmatic interface for interactions with InfluxDB.
Access the InfluxDB API using the `/api/v2/` endpoint.
menu: v2_0_ref
weight: 2
weight: 3
v2.0/tags: [api]
---

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name: Command line tools
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---
InfluxDB provides command line tools designed to aid in managing and working

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description: >
InfluxDB client libraries are language-specific tools that integrate with the InfluxDB v2 API.
View the list of available client libraries.
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v2_0_ref:
name: Client libraries

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v2_0_ref:
name: Configuration options
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---
To configure InfluxDB, use the following configuration options when starting the

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title: InfluxDB key concepts
description: >
Concepts related to InfluxDB.
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v2_0_ref:
name: Key concepts
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Before working with InfluxDB 2.0, it's helpful to learn a few key concepts, including:
- [InfluxDB data elements](#influxdb-data-elements)
{{< children >}}
<!-- - [InfluxDB data elements](#influxdb-data-elements)
- [InfluxDB table structure](#influxdb-layout)
- [InfluxDB design principles](/v2.0/reference/design-principles)
<!--- [InfluxDB platform](/v2.0/reference/) -->
<!--- [InfluxDB platform](/v2.0/reference/) --> -->
### InfluxDB data elements
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census bees=28i,ants=32i 1566086760000000000
-----------------
Field set
```
{{% note %}}
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| census | location=portland,scientist=mullen | ants |
A **series** includes timestamps and field values for a given series key. From the sample data, here's a **series key** and the corresponding **series**:
```bash
# series key
census,location=klamath,scientist=anderson bees
@ -197,6 +200,6 @@ An InfluxDB **organization** is a workspace for a group of [users](/v2.0/users/)
If you're just starting out, we recommend taking a look at the following guides:
- [Getting Started](/influxdb/v0.10/introduction/getting_started/)
- [Getting Started](/influxdb/v0.10/introduction/getting_started/)
- [Writing Data](/influxdb/v0.10/guides/writing_data/)
- [Querying Data](/influxdb/v0.10/guides/querying_data/)
- [Querying Data](/influxdb/v0.10/guides/querying_data/)

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---
title: InfluxDB data elements
description: >
InfluxDB structures data using elements such as timestamps, field keys, field values, tags, etc.
weight: 102
menu:
v2_0_ref:
parent: Key concepts
name: Data elements
v2.0/tags: [key concepts, schema]
---
InfluxDB 2.0 includes the following data elements:
- [timestamp](#timestamp)
- [field key](#field-key)
- [field value](#field-value)
- [field set](#field-set)
- [tag key](#tag-key)
- [tag value](#tag-value)
- [tag set](#tag-set)
- [measurement](#measurement)
- [series](#series)
- [point](#point)
- [bucket](#bucket)
- [organization](#organization)
The [sample data](#sample-data) below is used to illustrate data elements concepts.
_Hover over highlighted terms to get acquainted with InfluxDB terminology and layout._
**bucket:** `my_bucket`
| _time | _measurement | <span class ="tooltip" data-tooltip-text ="Tag key">location</span> | <span class ="tooltip" data-tooltip-text ="Tag key">scientist</span> | _field | _value |
|:------------------- |:------------ |:------- |:------ |:-- |:------ |
| 2019-08-18T00:00:00Z | census | klamath | anderson | bees | 23 |
| 2019-08-18T00:00:00Z | census | portland | mullen | ants | 30 |
| 2019-08-18T00:06:00Z | census | klamath | anderson | bees | 28 |
| <span class="tooltip" data-tooltip-text="Timestamp">2019-08-18T00:06:00Z</span> | <span class="tooltip" data-tooltip-text="measurement"> census</span> | <span class ="tooltip" data-tooltip-text ="Tag value">portland</span> | <span class ="tooltip" data-tooltip-text ="Tag value">mullen</span> | <span class ="tooltip" data-tooltip-text ="Field key">ants</span> | <span class ="tooltip" data-tooltip-text ="Field value">32</span> |
## Timestamp
All data stored in InfluxDB has a `_time` column that stores timestamps. On disk, timestamps are stored in epoch nanosecond format. InfluxDB formats timestamps show the date and time in [RFC3339](https://www.ietf.org/rfc/rfc3339.txt) UTC associated with data. Timestamp precision is important when you write data.
## Measurement
The `_measurement` column shows the name of the measurement `census`. Measurement names are strings. A measurement acts as a container for tags, fields, and timestamps. Use a measurement name that describes your data. The name `census` tells us that the field values record the number of `bees` and `ants`.
## Fields
A field includes a field key stored in the `_field` column and a field value stored in the `_value` column.
### Field key
A field key is a string that represents the name of the field. In the sample data above, `bees` and `ants` are field keys.
### Field values
A field value represents the value of an associated field. Field values can be strings, floats, integers, or booleans. The field values in the sample data show the number of `bees` at specified times: `23`, and `28` and the number of `ants` at a specified time: `30` and `32`.
### Field sets
A field set is a collection of field key-value pairs associated with a timestamp. The sample data includes the following field sets:
```bash
census bees=23i,ants=30i 1566086400000000000
census bees=28i,ants=32i 1566086760000000000
-----------------
Field set
```
{{% note %}}
**Fields aren't indexed:** Fields are required in InfluxDB data and are not indexed. Queries that filter field values must scan all field values to match query conditions. As a result, queries on tags > are more performant than queries on fields. **Store commonly queried metadata in tags.**
{{% /note %}}
## Tags
The columns in the sample data, `location` and `scientist`, are tags.
Tags include tag keys and tag values that are stored as strings and metadata.
### Tag keys
The tag keys in the sample data are `location` and `scientist`.
### Tag values
The tag key `location` has two tag values: `klamath` and `portland`.
The tag key `scientist` also has two tag values: `anderson` and `mullen`.
### Tag sets
The collection of tag key-value pairs make up a tag set. The sample data includes the following four tag sets:
```bash
location = klamath, scientist = anderson
location = portland, scientist = anderson
location = klamath, scientist = mullen
location = portland, scientist = mullen
```
{{% note %}}
**Tags are indexed:** Tags are optional. You don't need tags in your data structure, but it's typically a good idea to include tags.
Because tags are indexed, queries on tags are faster than queries on fields. This makes tags ideal for storing commonly-queried metadata.
{{% /note %}}
#### Why your schema matters
If most of your queries focus on values in the fields, for example, a query to find when 23 bees were counted:
```js
from(bucket: "bucket-name")
|> range(start: 2019-08-17T00:00:00Z, stop: 2019-08-19T00:00:00Z)
|> filter(fn: (r) => r._field == "bees" and r._value == 23)
```
InfluxDB scans every field value in the dataset for `bees` before the query returns a response. If our sample `census` data grew to millions of rows, to optimize your query, you could rearrange your [schema](/v2.0/reference/glossary/#schema) so the fields (`bees` and `ants`) becomes tags and the tags (`location` and `scientist`) become fields:
| _time | _measurement | <span class ="tooltip" data-tooltip-text ="Tag key">bees</span> | _field | _value |
|:------------------- |:------------ |:------- |:-- |:------ |
| 2019-08-18T00:00:00Z | census | 23 | location | klamath |
| 2019-08-18T00:00:00Z | census | 23 | scientist | anderson |
| 2019-08-18T00:06:00Z | census | <span class ="tooltip" data-tooltip-text ="Tag value">28</span> | <span class ="tooltip" data-tooltip-text ="Field key">location</span> | <span class ="tooltip" data-tooltip-text ="Field value">klamath</span> |
| 2019-08-18T00:06:00Z | census | 28 | scientist | anderson |
| _time | _measurement | <span class ="tooltip" data-tooltip-text ="Tag key">ants</span> | _field | _value |
|:------------------- |:------------ |:------- |:-- |:------ |
| 2019-08-18T00:00:00Z | census | 30 | location | portland |
| 2019-08-18T00:00:00Z | census | 30 | scientist | mullen |
| 2019-08-18T00:06:00Z | census | <span class ="tooltip" data-tooltip-text ="Tag value">32</span> | <span class ="tooltip" data-tooltip-text ="Field key">location</span> | <span class ="tooltip" data-tooltip-text ="Field value">portland</span>|
| 2019-08-18T00:06:00Z | census | 32 | scientist | mullen |
Now that `bees` and `ants` are tags, InfluxDB doesn't have to scan all `_field` and `_value` columns. This makes your queries faster.
## Series
Now that you're familiar with measurements, field sets, and tag sets, it's time to discuss series keys and series. A **series key** is a collection of points that share a measurement, tag set, and field key. For example, the [sample data](#sample-data) includes two unique series keys:
| _measurement | tag set | _field |
|:------------- |:------------------------------- |:------ |
| census | <span class="tooltip" data-tooltip-text="Tag set">location=klamath,scientist=anderson</span> |<span class="tooltip" data-tooltip-text="Field key">bees</span>|
| census | location=portland,scientist=mullen | ants |
A **series** includes timestamps and field values for a given series key. From the sample data, here's a **series key** and the corresponding **series**:
```bash
# series key
census,location=klamath,scientist=anderson bees
# series
2019-08-18T00:00:00Z 23
2019-08-18T00:06:00Z 28
```
Understanding the concept of a series is essential when designing your [schema](v2.0/reference/glossary/#schema) and working with your data in InfluxDB.
## Point
A **point** includes the series key, a field value, and a timestamp. For example, a single point from the [sample data](#sample-data) looks like this:
`2019-08-18T00:00:00Z census ants 30 portland mullen`
## Bucket
All InfluxDB data is stored in a bucket. A **bucket** combines the concept of a database and a retention period (the duration of time that each data point persists). A bucket belongs to an organization. For more information about buckets, see [Manage buckets](https://v2.docs.influxdata.com/v2.0/organizations/buckets/).
## Organization
An InfluxDB **organization** is a workspace for a group of [users](/v2.0/users/). All [dashboards](/v2.0/visualize-data/dashboards/), [tasks](/v2.0/process-data/), buckets, and users belong to an organization. For more information about organizations, see [Manage organizations](https://v2.docs.influxdata.com/v2.0/organizations/).
If you're just starting out, we recommend taking a look at the following guides:
- [Getting Started](/influxdb/v0.10/introduction/getting_started/)
- [Writing Data](/influxdb/v0.10/guides/writing_data/)
- [Querying Data](/influxdb/v0.10/guides/querying_data/)

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title: InfluxDB design principles
description: >
Principles and tradeoffs related to InfluxDB design.
weight: 7
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menu:
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parent: Key concepts
name: Design principles
v2.0/tags: [key concepts, design principles]
---

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---
title: InfluxDB data elements
description: >
InfluxDB uses a columnar system to structure tables.
weight: 103
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parent: Key concepts
name: Table structure
v2.0/tags: [key concepts]
---
InfluxDB 2.0 uses the following columnar table structure to store data:
- **Annotation rows:** include the following rows: #group, #datatype, and #default.
- **Header row:** describes the data labels for each column in a row.
- **Data columns:** include the following columns: annotation, result, and table.
- **Data rows:** all rows that contain time series data. See [sample data](#sample-data) below.
For specifications on the InfluxDB 2.0 table structure, see [Tables](/v2.0/reference/annotated-csv/#tables).
**_Tip:_** To visualize your table structure in the InfluxDB user interface, click the **Data Explorer** icon
in the sidebar, create a query, click **Submit**, and then select **View Raw Data**.