# Working with several streams in a query

In this section we will go through how to use one of the stream
merging functions, `pivot`

, to combine several streams in a
query. This tutorial might help you if you are working with streams of
several signals and would like to combine and compare them.

## Pivot streamsâ€‹

The function `pivot`

transforms a vector of streams $VS$ into
a *pivoted* stream of vectors $PS$ where each element $PS_i$ is the
most recently received value from some stream $VS_i$ in $VS$.

`doc("pivot")`

Let's start with a *degenerate* example where we only merge one stream:

`select pivot`

from Stream of Vector pivot

where pivot in pivot([simstream(.02)])

Now let's expand this example by pivoting two streams:

`select v`

from Stream of Vector pivot, Vector of Stream vs, Vector v

where vs = [1+simstream(0.02), 2+simstream(.2)]

and pivot = pivot(vs)

and v in pivot

limit 14

Notice that the first vector contains a `null`

value. This is
because the pivoted stream had not received any value from stream 2
when it received the first value from stream 1. This can be avoided
by using a pivot streams variant that takes an extra argument being
the initial vector in the result stream:

`select v`

from Stream of Vector pivot, Vector of Stream vs, Vector v

where vs = [1+simstream(0.02), 2+simstream(.2)]

and pivot = pivot(vs, zeros(dim(vs)))

and v in pivot

limit 14

The following is an example of a more advanced stream pivot:

`select pivot`

from Stream of Vector pivot,

Vector of Stream vs,

Stream heartbeat_mod,

Stream fast_heartbeat_mod

where vs = [

simstream(0.02),

3+simstream(.2),

heartbeat_mod,

fast_heartbeat_mod

]

and heartbeat_mod = 1 - 2*mod(heartbeat(1), 2)

and fast_heartbeat_mod = mod(round(10*heartbeat(.1)), 2)

and pivot = pivot(vs, zeros(dim(vs)))

### Arithmetics on combined streams!â€‹

If you want to run arithmetics on pivoted streams you first need
to extract the vectors from the pivoted stream. This is done with the
line `v in ps`

in the query below.

`//plot: Line plot`

select v[1]*v[4] + v[3]*10, v[4], v[2]

from Stream of Vector sv,

Vector of Stream vs,

Stream hbmod,

Stream hbmodfast,

Vector of Number v

where hbmod = 1 - 2*mod(heartbeat(1), 2)

and hbmodfast = mod(round(10*heartbeat(.1)), 2)

and vs = [simstream(0.02), 3+3*simstream(.2), hbmod, hbmodfast]

and sv = pivot(vs, zeros(dim(vs)))

and v in sv

Let's smooth that `v[2]`

`//plot: Line plot`

select v[1]*v[4] + v[3]*10, v[4], mean(win)

from Stream of Vector sv,

Vector of Stream vs,

Stream hbmod,

Stream hbmodfast,

Vector of Number v,

Vector of Number win

where hbmod = 1 - 2*mod(heartbeat(1), 2)

and hbmodfast = mod(round(10*heartbeat(.1)), 2)

and vs = [simstream(0.02), winagg(3+3*simstream(.2),10,1),

hbmod, hbmodfast]

and sv = pivot(vs, zeros(dim(vs)))

and v in sv

and win = v[2]

The following two queries seem to be defined in the same way, but they do give rise to different behavior:

`//plot: Multi plot`

{'sa_plot': 'Scatter plot', 'labels':['x','y'], 'memory': 1000};

pivot([sin(10*heartbeat(.01)),

cos(10*heartbeat(.01))])

`//plot: Multi plot`

{'sa_plot': 'Scatter plot', 'labels':['x','y'], 'memory': 1000};

select sin(x), cos(x)

from Number x

where x in 10*heartbeat(.02)

The first query differs slightly since it uses two
*independent* streams together with pivot streams, This means that we
essentially have two streams where `sin`

and `cos`

are applied to
their own stream over time (heartbeat) before they are merged.

In the second example we apply `sin`

and `cos`

to the `x`

from the
*same* `heartbeat`

stream.

More examples of how we can specify multiple streams in a query:

`//plot: Multi plot`

{'sa_plot': 'Line plot', 'memory': 200};

select pivot([sin(hb), sin(hb+pi())])

from Stream of Number hb

where hb = 10*heartbeat(.02)

`//plot: Multi plot`

{'sa_plot': 'Bar plot', 'memory': 200};

pivot(select Vector of sin(i/3 + 3*heartbeat(.03))

from Integer i

where i in iota(0,29)

order by i

)

Hopefully these short examples has made you understand how you can combine streams using pivot streams.

The next part of the tutorial shows how to develop
**data stream wrappers** to enable easy access and understanding of
external data streams by defining meta-data (ontologies) describing
properties of the streams.