# GA4 events

> A Google Analytics 4 export is one table per day with every event's parameters packed into a repeated STRUCT. Querylab.io recognises the dataset, collapses the shards into one node, and shows which events and parameters are actually in the data (sampled for free), with the UNNEST snippets ready to paste.

Source: https://docs.querylab.io/schema-browser/ga4-events/

**tree**

analytics_<property id> gets the GA4 icon. Daily shards and intraday shards collapse into one node each, with the shard count.

## How the export is recognised

A dataset named `analytics_<digits>` is treated as a GA4 export; the digits are the property ID. Inside it, `events_YYYYMMDD` is the daily export and `events_intraday_YYYYMMDD` the streaming export for the current day.

## The shard group

Any table whose name ends in a date (`_YYYYMMDD`, `_YYYYMM`, `_YYYYMMDDHH`) is grouped with its siblings into a single tree node, `events (412)`. This applies to every sharded table, not just GA4. Opening the node shows the schema of the newest shard and a **Sharded Table Info** group on the Details tab:

The wildcard query has **Copy to clipboard** and **Open in new tab** buttons; **Discover partitions** generates an `INFORMATION_SCHEMA.TABLES` query that lists every shard with its size. Row counts and bytes in Storage info are summed across the shards.

## Seeing which events are in the data

Which events are in the table, from a free 1,000-row sample:

The banner says how many rows were sampled. Run query to get all values re-runs it as a real, billed GROUP BY.

Descriptions come from Google's documentation for the automatically collected and recommended events; custom events show no description. Counts are of the sample, so treat them as proportions. **Run query to get all values** shows the estimated cost, then replaces the sample with exact counts; the **% of Sample** column disappears because it no longer applies.

## Pulling parameters out of event_params

The keys inside `event_params`, with the value type each one uses:

**Source** tells you where the row came from: **Built-in** parameters are the ones GA4 documents (they are listed even if the sample did not contain them, when **Show all built-in params** is on); **Sampled** parameters were found in the data and are usually your custom ones. A custom parameter that occurs rarely may be missing from a 1,000-row sample; the banner says so, and **Run query to get all values** fixes it.

The tab's main output is SQL. Clicking a row's **Insert** button (or **Copy SQL**) produces the subquery for that key, typed correctly:

```sql
(SELECT value.string_value FROM UNNEST(event_params) WHERE key = 'page_location') AS page_location
```

Select several rows and **Insert N Selected** inserts them as a comma-separated list in the active query tab. The **Snippets** menu inserts a template instead — **Extract String**, **Extract Integer**, **Extract Double**, **Extract Float**, **Extract Any Type** (a `COALESCE` over all four value columns) or **Extract Multiple (Template)**.

## Writing the query

Filter on `_TABLE_SUFFIX` and `event_name` first; both prune before any bytes are read. Then unnest what you need:

```sql
SELECT
  event_date,
  event_name,
  (SELECT value.string_value FROM UNNEST(event_params) WHERE key = 'page_location') AS page_location,
  (SELECT value.int_value FROM UNNEST(event_params) WHERE key = 'ga_session_id') AS session_id
FROM `ace-analytics.analytics_388475286.events_*`
WHERE _TABLE_SUFFIX BETWEEN '20260801' AND '20260828'
  AND event_name = 'page_view'
```

The Schema tab fills in Google's description for the export's built-in columns when the table itself has none, so columns such as `user_pseudo_id` or `privacy_info` come with an explanation.

## Extra menu items on a GA4 dataset

Right-click a GA4 dataset for two extra entries under a **Google Analytics 4** divider:

- **GA4 Templates**: ready-made queries for the property: Events by Date, Top Events, Daily Active Users, Page Views by URL, User Acquisition, User Engagement, Users by Device, Users by Geography, Revenue by Item, Purchase Funnel, Transactions, and explorers for `event_params`, `user_properties`, `items` and the expanded-export tables. Each opens in a new tab with the dataset filled in.
- **GA4 Model Generator**: opens a tab that generates analysis-ready tables from the raw export: session-scoped attribution with gclid correction, channel grouping, custom parameter columns, conversion events, RFM segments, with multi-property support and a configurable date range.

The dataset's Details tab also shows the **Property ID**, whether **Events Export** and **Intraday Streaming** are present, the **Last Export Date**, and a **View in Google Analytics** link.