Optimising a query (Min, Max, First and Last) - influxdb

Question

First post here and new to InfluxDB.
I have been given the following query, and I have no clue how I can optimize it.
A period of 24 hours and 1m windows takes around 2.4 seconds at the moment (is this the expected amount of time).
I suspect one of the reasons is that there are 4 tables (querying the same set of data) and 3 joins.
I have looked into the map function to try and reduce it to one table but I can't seem to get it to work with the window.
bucketName = "${bucket}"
startTime = -${period}
interval = ${interval}
token = "${token}"
minPrice = from (bucket: bucketName)
|> range(start: startTime, stop: now())
|> filter(fn: (r) => r["_field"] == token)
|> window(every: interval)
|> min()
|> duplicate(column: "_value", as: "low")
|> keep(columns: ["low", "_start", "_stop"] )
maxPrice = from (bucket: bucketName)
|> range(start: startTime, stop: now())
|> filter(fn: (r) => r["_field"] == token)
|> window(every: interval)
|> max()
|> duplicate(column: "_value", as: "high")
|> keep(columns: ["high", "_start", "_stop"] )
openPrice = from (bucket: bucketName)
|> range(start: startTime, stop: now())
|> filter(fn: (r) => r["_field"] == token)
|> window(every: interval)
|> first()
|> duplicate(column: "_value", as: "open")
|> keep(columns: ["open", "_stop", "_start"] )
closePrice = from (bucket: bucketName)
|> range(start: startTime, stop: now())
|> filter(fn: (r) => r["_field"] == token)
|> window(every: interval)
|> last()
|> duplicate(column: "_value", as: "close")
|> keep(columns: ["close", "_stop", "_start"] )
highLowData = join(tables: {min: minPrice, max: maxPrice}, on: ["_start", "_stop"])
openCloseData = join(tables: {open: openPrice, close: closePrice}, on: ["_start", "_stop"])
join(tables: {highLow: highLowData, openClose: openCloseData}, on: ["_start", "_stop"])
I have managed to optimize it down to 0.7s by using a union rather than a join. However now I'm faced with data that has empty fields.
Like this:
Query below
startTime = -24h
breakDown = 1m
token = "tokenName"
all = from (bucket: "prices")
|> range(start: startTime, stop: now())
|> filter(fn: (r) => r["_field"] == token)
|> window(every: breakDown)
lowPrice = all
|> min()
|> duplicate(column: "_value", as: "low")
|> keep(columns: ["low", "_stop", "_start"] )
highPrice = all
|> max()
|> duplicate(column: "_value", as: "high")
|> keep(columns: ["high", "_stop", "_start"] )
openPrice = all
|> first()
|> duplicate(column: "_value", as: "open")
|> keep(columns: ["open", "_stop", "_start"] )
closePrice = all
|> last()
|> duplicate(column: "_value", as: "close")
|> keep(columns: ["close", "_stop", "_start"] )
highLowData = union(tables: [lowPrice, highPrice])
openCloseData = union(tables: [openPrice, closePrice])
result = union(tables: [highLowData, openCloseData])
|> yield (name: "Result")