I'd like to explore a Google Analytics 360 data with `bigrquery` using `dplyr` syntax (rather than SQL), if possible. The gist is that I want to understand user journeys—I'm interested in finding the most common sequences of pages at the user level (even across sessions).

I thought I could do it this way:

```
sample_query <- ga_sample %>%
  select(fullVisitorId, date, visitStartTime, totals, channelGrouping,
  hits.page.pagePath) %>% 
  collect()

```

But I get an error that `hits.page.pagePath` was not found. Then I tried:

```
sample_query <- ga_sample %>%
  select(fullVisitorId, date, visitStartTime, totals, channelGrouping, hits) %>% 
  collect() %>% 
  unnest_wider(hits)

```

But the result is `Error: Requested Resource Too Large to Return [responseTooLarge]`, which makes perfect sense. 

From what I've gathered, with the SQL syntax, the workaround is to `unnest` remotely, and `select` only the `hits.page.pagePath` field (rather than the entire `hits` top-level field). 

E.g., something like this (which is a different query, but conveys the point):

```
SELECT
  hits.page.pagePath
FROM
  'bigquery-public-data.google_analytics_sample.ga_sessions_20160801' AS GA,
  UNNEST(GA.hits) AS hits
GROUP BY
  hits.page.pagePath

```

Is it possible to do something similar with `dplyr` syntax? If it's not possible, what's the best approach with SQL?

Thanks!

**Update: Actual query/code**

```
SELECT DISTINCT
fullVisitorId, visitId, date, visitStartTime, hits.page.pagePath, hits.time, geoNetwork.networkDomain
FROM 'bigquery-public-data.google_analytics_sample.ga_sessions_*' AS GA, UNNEST(GA.hits) AS hits
WHERE _TABLE_SUFFIX BETWEEN "20191101" AND "20191102"
AND geoNetwork.networkDomain NOT LIKE "%google%"

```