# LogQL

## Video Lecture

## Description

Now that we have a loki data source we can query it with the LogQL query language.

In this video, we will try out many LogQL queries in the `systemd-journal`

stream selector that we just set up.

There are two types of LogQL queries:

- Log queries returning the contents of log lines as streams.
- Metric queries that convert logs into value matrixes.

A LogQL query consists of,

- The log stream selector
- Filter expression

We can use operations on both the log stream selectors and filter expressions to refine them.

### Log Stream Selectors

#### Operators

- = : equals
- != : not equals
- =~ : regex matches
- !~ : regex does not match

##### Examples

Return all log lines for the job `systemd-journal`

{job="systemd-journal"}

Return all log lines for the unit `ssh.service`

{unit="ssh.service"}

Return all log lines for the job `systemd-journal`

and the unit `cron.service`

{job="systemd-journal",unit="cron.service"}

Show all log lines for 2 jobs with different names

{job=~"sbcode/systemd-journal|systemd-journal"}

### Filter Expressions

#### Operators

Used for testing text within log line streams.

- |= : equals
- != : not equals
- |~ : regex matches
- !~ : regex does not match

##### Examples

Return lines including the text "error"

{job="systemd-journal"} |= "error"

Return lines **not** including the text "error"

{job="systemd-journal"} != "error"

Return lines including the text "error" or "info" using regex

{job="systemd-journal"} |~ "error|info"

Return lines **not** including the text "error" or "info" using regex

{job="systemd-journal"} !~ "error|info"

Return lines including the text "error" but **not** including "info"

{job="systemd-journal"} |= "error" != "info"

Return lines including the text "Invalid user" and including ("paulo" or "redis") using regex

{job="systemd-journal"} |~ "Invalid user (paulo|redis)"

Return lines including the text "status 403" or "status 503" using regex

{job="systemd-journal"} |~ "status [45]03"

#### Range and Instance Vectors

The data so far is returned as streams of log lines. We can graph these in visualisations if we convert them to vectors. We can aggregate the lines into numeric values, such as counts, which then become known as instance or range vectors.

- count_over_time : Shows the total count of log lines for time range
- rate : Similar as
*count_over_time*but converted to number of entries per second - bytes_over_time : Number of bytes in each log stream in the range
- bytes_rate : Similar to
*bytes_over_time*but converted to number of bytes per second

##### Examples

The count of jobs at 1 minutes time intervals

count_over_time({job="systemd-journal"}[1m])

The rate of logs per minute. Rate is similar to `count_over_time`

but shows the entries per second.

rate({job="systemd-journal"}[1m])

Info

rate = count_over_time / 60 / range(m)

eg,

`12 / 60 / 2 = 0.1`

The count of `errors`

at 1h time intervals

count_over_time({job="systemd-journal"} |= "error" [1h])

#### Aggregate Functions

An aggregate function converts a range vector result into a single instance vector.

- sum : Calculate the total of all instance vectors in the range at time
- min : Show the minimum value from all instance vectors in the range at time
- max : Show the maximum value from all instance vectors in the range at time
- avg : Calculate the average of the values from all instance vectors in the range at time
- stddev : Calculate the standard deviation of the values from all instance vectors in the range at time
- stdvar : Calculate the standard variance of the values from all instance vectors in the range at time
- count : Count the number of elements all all instance vectors in the range at time
- bottomk : Select lowest k values in all the instance vectors in the range at time
- topk : Select highest k values in all the instance vectors in the range at time

Note

**bottomk** and **topk** don't produce an instance vector, but a range vector of containing the k number of instance vectors in the time range.

##### Examples

Calculate the total of all instance vectors in the range at time

sum(count_over_time({job="systemd-journal"}[1m]))

Show the minimum value from all instance vectors in the range at time

min(count_over_time({job="systemd-journal"}[1m]))

Show the maximum value from all instance vectors in the range at time

max(count_over_time({job="systemd-journal"}[1m]))

Show only the top 2 values from all instance vectors in the range at time

topk(2, count_over_time({job="systemd-journal"}[1h]))

#### Aggregate Group

Convert an instance vector into a range vector organised by unit

##### Examples

Group a single log stream by unit

sum(count_over_time({job="systemd-journal"}[1m])) by (unit)

Group multiple log streams by job

sum(count_over_time({job=~"sbcode/systemd-journal|systemd-journal"}[1m])) by (job)

Group multiple log streams and specific unit by job

sum(count_over_time({job=~"sbcode/systemd-journal|systemd-journal", unit="cron.service"}[1m])) by (job)

Group multiple log streams by job and unit

sum(count_over_time({job=~"sbcode/systemd-journal|systemd-journal"}[1m])) by (job,unit)

#### Comparison Operators

Comparison Operators. Used for testing numeric values present in scalars and vectors.

- == (equality)
- != (inequality)
- > (greater than)
- >= (greater than or equal to)
- < (less than)
- <= (less than or equal to)

##### Examples

Returns values greater than 4

sum(count_over_time({job="systemd-journal"}[1m])) > 4

Returns values less than or equal to 1

sum(count_over_time({job="systemd-journal"}[1m])) <= 1

#### Logical Operators

These can be applied to both range and instance vectors

- and : Bother sides must be true
- or : Either side must be true
- unless : Return values unless value

##### Examples

Returns values greater than 4 or values less then or equal to 1

sum(count_over_time({job="systemd-journal"}[1m])) > 4 or sum(count_over_time({job="systemd-journal"}[1m])) <= 1

Return values between 2 and 5

sum(count_over_time({job="systemd-journal"}[1m])) > 2 and sum(count_over_time({job="systemd-journal"}[1m])) < 5

#### Arithmetic Operators

- + : Add
- - : Subtract
- * : Multiply
- / : Divide
- % : Modulus
- ^ : Power/Exponentiation

##### Examples

sum(count_over_time({job="systemd-journal"}[1m])) * 10 sum(count_over_time({job="systemd-journal"}[1m])) % 2

#### Operator order

Many Operators can be used at a time. The order follows the PEMDAS construct. PEMDAS is an acronym for the words parenthesis, exponents, multiplication, division, addition, subtraction.

##### Examples

A nonsensical example

sum(count_over_time({job="systemd-journal"}[1m])) % 4 * 2 ^ 2 + 2 # is the same as ((sum(count_over_time({job="systemd-journal"}[1m])) % 4 * (2 ^ 2)) + 2)

Proving that count_over_time / 60 / range(m) = rate

rate({job="systemd-journal"}[2m]) == count_over_time({job="systemd-journal"}[2m]) / 60 / 2 # is the same as rate({job="systemd-journal"}[2m]) == ((count_over_time({job="systemd-journal"}[2m]) / 60) / 2)