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‎docs/enterprise_edition/active_queries.md‎

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---
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icon: material/play-circle
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---
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# Running queries
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PgDog EE provides a real-time view into queries currently executing on PostgreSQL connections. It is accessible in two places:
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1. [`SHOW ACTIVE_QUERIES`](#admin-database) admin command
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2. [Activity](#dashboard) view in the dashboard
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## How it works
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When a client sends a query to PgDog, it will first attempt to acquire a connection from the connection pool. Once acquired, it will register the query with the live query view. After the query finishes running, it's removed from the view.
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Only queries that are currently executing through PgDog are visible in this view. If your application doesn't connect to PgDog, its queries won't appear here.
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### Admin database
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You can see which queries are actually running on each instance by connecting to the admin database and running the `SHOW ACTIVE_QUERIES` command:
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=== "Command"
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```
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SHOW ACTIVE_QUERIES;
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```
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=== "Output"
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```
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query | protocol | database | user | running_time |
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-------------------------------------------------------+----------+----------+-------+--------------+
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SELECT * FROM users WHERE id = $1 | extended | pgdog | pgdog | 15 |
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SELECT pg_sleep(50) | simple | pgdog | pgdog | 5 |
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INSERT INTO users (id, email) VALUES ($1, $2) | extended | pgdog | pgdog | 1 |
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```
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The following information is available in the running queries view:
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| Column | Description |
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|-|-|
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| `query` | The SQL statement currently executing on a PostgreSQL connection. |
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| `protocol` | What version of the query protocol is used. `simple` protocol injects parameters into text, while `extended` is used by prepared statements. |
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| `database` | The name of the connection pool database. |
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| `user` | The name of the user executing the query. |
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| `running_time` | For how long (in ms) has the query been running. |
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### Dashboard
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If you're running multiple instances of PgDog, active queries from all instances are aggregated and sent to the Dashboard application. They are then made available in the Activity tab, in real-time, with query plans automatically attached for slow queries.
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<center>
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<img src="/images/ee/activity.png" width="100%" alt="How PgDog works" class="screenshot" />
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<i>Real-time view into running queries.</i>
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</center>

‎docs/enterprise_edition/index.md‎

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---
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icon: material/office-building
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---
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# PgDog EE
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PgDog **E**nterprise **E**dition is a version of PgDog that contains additional features for at scale monitoring and deployment of sharded (and unsharded) PostgreSQL databases.
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Unlike PgDog itself, PgDog EE is closed source and available upon the purchase of a license. It comes with a hosted management dashboard which provides real-time visibility into PgDog's operations.
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## Features
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| Feature | Description |
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|-|-|
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| [Running queries](active_queries.md) | Instant view into queries running through PgDog. |
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| [Query plans](query_plans.md) | Root cause slow queries in seconds with automatic PostgreSQL query plans. |
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| [Real-time metrics](metrics.md) | All PgDog metrics, delivered with second-precision through a dedicated link. |
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| Query blocker | Terminate all instances of a slow query with a button click and prevent them from running again. |
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## Get a demo
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If you'd like a demo of PgDog EE, [get in touch](https://calendly.com/lev-pgdog/30min) with our sales team. PgDog EE comes with a [cloud](https://cloud.pgdog.dev) deployment managed by us, or can be deployed entirely on-prem.

‎docs/enterprise_edition/metrics.md‎

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---
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icon: material/speedometer
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---
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# Real-time metrics
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PgDog EE collects and sends its own metrics to the Dashboard. This provides a real-time view into PgDog internals, without a delay that's typically present in other monitoring solutions.
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## How it works
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Real-time metrics are available in both Open Source and Enterprise versions of PgDog. The [open source metrics](../features/metrics.md) are accessible via an OpenMetrics endpoint or via the admin database.
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In PgDog EE, the same metrics are collected and sent via a dedicated uplink to the Dashboard. This provides an out-of-the-box experience for monitoring deployments, without delays typically introduced by other solutions.
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<center>
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<img src="/images/ee/metrics.png" width="100%" alt="How PgDog works" class="screenshot" />
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<i>Real-time metrics.</i>
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</center>
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Since metrics are just integers, they can be serialized and sent efficiently. To deliver second-precision metrics, PgDog EE requires less than 1KB/second of bandwidth and basically no CPU or additional memory.
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Once the metrics reach the Dashboard, they are pushed down to the web UI via a WebSocket connection. At the same time, per-minute aggregates are computed in the background and stored in a separate Postgres database. This provides a historical view into database performance.

‎docs/enterprise_edition/query_plans.md‎

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---
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icon: material/chart-timeline
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---
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# Query plans
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For any [running query](active_queries.md) exceeding a configurable time threshold, PgDog EE will ask Postgres for a query plan. The query plans are stored in their own view, accessible via two methods:
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1. [`SHOW QUERY_PLANS`](#admin-database) admin command
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2. [Activity](active_queries.md#dashboard) view in the dashboard
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## How it works
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When a [running query](active_queries.md) exceeds a configurable threshold, PgDog EE will ask Postgres for its query plan by sending an `EXPLAIN` command via a dedicated connection. For prepared statements, PgDog automatically provides the parameters sent with the statement by the client.
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Since `EXPLAIN` itself is very quick, fetching and storing query plans is efficient and doesn't impact database performance. Nonetheless, to avoid planning queries unnecessarily, the plans are stored in an in-memory cache. Old plans are evicted automatically and recomputed.
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### Admin database
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The query plans are accessible by connecting to the admin database and running the `SHOW QUERY_PLANS` command:
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=== "Command"
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```
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SHOW QUERY_PLANS;
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```
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=== "Output"
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```
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query | plan | database | user | age
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-------------------------------------------------------+-------------------------------------------------------------------------------------------------------------------------+----------+-------+---------
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select pg_sleep(50); | Result (cost=0.00..0.01 rows=1 width=4) | pgdog | pgdog | 6984139
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SELECT abalance FROM pgbench_accounts WHERE aid = $1; | Index Scan using pgbench_accounts_pkey on pgbench_accounts (cost=0.29..8.31 rows=1 width=4) Index Cond: (aid = 96934) | pgdog | pgdog | 7711
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(2 rows)
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```
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The following information is available in this view:
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| Column | Description |
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|-|-|
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| `query` | The query for which the plan is prepared. |
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| `plan` | The query plan fetched directly from PostgreSQL. |
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| `database` | The name of the connection pool database. |
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| `user` | The name of the user running the query. |
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| `age` | How long ago the plan was fetched from Postgres (in ms). |
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### Dashboard
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The query plans are automatically attached to running queries and sent to the Dashboard via a dedicated connection. They can be viewed in real-time in the [Activity](active_queries.md#dashboard) tab.

‎docs/images/ee/activity.png‎

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‎docs/images/ee/metrics.png‎

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‎docs/style.css‎

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.md-header {
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--md-primary-fg-color: rgb(7, 81, 207);
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}
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.screenshot {
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border-radius: 8px;
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}

‎tests/test_code_blocks.py‎

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import sys
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import pglast
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from regex import sub
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from regex.regex import Regex, RegexFlag
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mdp = MarkdownIt()
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pattern = re.compile(

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