The Dataflow Model
In Zed, each operator takes its input from the output of its upstream operator beginning either with a data source or with an implied source.
All available operators are listed on the reference page.
Dataflow Sources
In addition to the data sources specified as files on the zq
command line,
a source may also be specified with the from
operator.
When running on the command-line, from
may refer to a file, an HTTP
endpoint, or an S3 URI. When running in a Zed lake, from
typically
refers to a collection of data called a "data pool" and is referenced using
the pool's name much as SQL references database tables by their name.
For more detail, see the reference page of the from
operator,
but as an example, you might use the get
form of from
to fetch data from an
HTTP endpoint and process it with Zed, in this case, to extract the description
and license of a GitHub repository:
zq -f text "get https://api.github.com/repos/brimdata/zed | yield description,license.name"
When a Zed query is run on the command-line with zq
, the from
source is
typically omitted and implied instead by the command-line file arguments.
The input may be stdin via -
as in
echo '"hello, world"' | zq -
The examples throughout the language documentation use this "echo pattern"
to standard input of zq -
to illustrate language semantics.
Note that in these examples, the input values are expressed as Zed values serialized
in the ZSON text format
and the zq
query text expressed as the first argument of the zq
command
is expressed in the syntax of the Zed language described here.
Dataflow Operators
Each operator is identified by name and performs a specific operation on a stream of records.
Some operators, like
summarize
or sort
,
read all of their input before producing output, though
summarize
can produce incremental results when the group-by key is
aligned with the order of the input.
For large queries that process all of their input, time may pass before seeing any output.
On the other hand, most operators produce incremental output by operating
on values as they are produced. For example, a long running query that
produces incremental output will stream results as they are produced, i.e.,
running zq
to standard output will display results incrementally.
The search
and where
operators "find" values in their input and drop
the ones that do not match what is being looked for.
The yield
operator emits one or more output values
for each input value based on arbitrary expressions,
providing a convenient means to derive arbitrary output values as a function
of each input value, much like the map concept in the MapReduce framework.
The fork
operator copies its input to parallel
legs of a query. The output of these parallel paths can be combined
in a number of ways:
- merged in sorted order using the
merge
operator, - joined using the
join
operator, or - combined in an undefined order using the implied
combine
operator.
A path can also be split to multiple query legs using the
switch
operator, in which data is routed to only one
corresponding leg (or dropped) based on the switch clauses.
Switch operators typically
involve multiline Zed programs, which are easiest to edit in a file. For example,
suppose this text is in a file called switch.zed
:
switch this (
case 1 => yield {val:this,message:"one"}
case 2 => yield {val:this,message:"two"}
default => yield {val:this,message:"many"}
) | merge val
Then, running zq
with -I switch.zed
like so:
echo '1 2 3 4' | zq -z -I switch.zed -
produces
{val:1,message:"one"}
{val:2,message:"two"}
{val:3,message:"many"}
{val:4,message:"many"}
Note that the output order of the switch legs is undefined (indeed they run
in parallel on multiple threads). To establish a consistent sequence order,
a merge
operator
may be applied at the output of the switch specifying a sort key upon which
to order the upstream data. Often such order does not matter (e.g., when the output
of the switch hits an aggregator), in which case it is typically more performant
to omit the merge (though the Zed system will often delete such unnecessary
operations automatically as part optimizing queries when they are compiled).
If no merge
or join
is indicated downstream of a fork
or switch
,
then the implied combine
operator is presumed. In this case, values are
forwarded from the switch to the downstream operator in an undefined order.
The Special Value this
In Zed, there are no looping constructs and variables are limited to binding values between lateral scopes. Instead, the input sequence to an operator is produced continuously and any output values are derived from input values.
In contrast to SQL, where a query may refer to input tables by name,
there are no explicit tables and a Zed operator instead refers
to its input values using the special identifier this
.
For example, sorting the following input
echo '"foo" "bar" "BAZ"' | zq -z sort -
produces this case-sensitive output:
"BAZ"
"bar"
"foo"
But we can make the sort case-insensitive by applying a function to the
input values with the expression lower(this)
, which converts
each value to lower-case for use in in the sort without actually modifying
the input value, e.g.,
echo '"foo" "bar" "BAZ"' | zq -z 'sort lower(this)' -
produces
"bar"
"BAZ"
"foo"
Implied Field References
A common use case for Zed is to process sequences of record-oriented data (e.g., arising from formats like JSON or Avro) in the form of events or structured logs. In this case, the input values to the operators are Zed records and the fields of a record are referenced with the dot operator.
For example, if the input above were a sequence of records instead of strings and perhaps contained a second field, e.g.,
{s:"foo",x:1}
{s:"bar",x:2}
{s:"BAZ",x:3}
Then we could refer to the field s
using this.s
and sort the records
as above with sort this.s
, which would give
{s:"BAZ",x:3}
{s:"bar",x:2}
{s:"foo",x:1}
This pattern is so common that field references to this
may be shortened
by simply referring to the field by name wherever a Zed expression is expected,
e.g.,
sort s
is shorthand for sort this.s
Field Assignments
A typical operation in records involves
adding or changing the fields of a record using the put
operator
or extracting a subset of fields using the cut
operator.
Also, when aggregating data using group-by keys, the group-by assignments
create new named record fields.
In all of these cases, the Zed language uses the token :=
to denote
field assignment. For example,
put x:=y+1
or
summarize salary:=sum(income) by address:=lower(address)
This style of "assignment" to a record value is distinguished from the =
token which binds a locally scoped name to a value that can be referenced
in later expressions.
Implied Operators
When Zed is run in an application like Zui, queries are often composed interactively in a "search bar" experience. The language design here attempts to support both this "lean forward" pattern of usage along with a "coding style" of query writing where the queries might be large and complex, e.g., to perform transformations in a data pipeline, where the Zed queries are stored under source-code control perhaps in GitHub or in Zui's query library.
To facilitate both a programming-like model as well as an ad hoc search
experience, Zed has a canonical, long form that can be abbreviated
using syntax that supports an agile, interactive query workflow.
To this end, Zed allows certain operator names to be optionally omitted when
they can be inferred from context. For example, the expression following
the summarize
operator
summarize count() by id
is unambiguously an aggregation and can be shortened to
count() by id
Likewise, a very common lean-forward use pattern is "searching" so by default, expressions are interpreted as keyword searches, e.g.,
search foo bar or x > 100
is abbreviated
foo bar or x > 100
Furthermore, if an operator-free expression is not valid syntax for
a search expression but is a valid Zed expression,
then the abbreviation is treated as having an implied yield
operator, e.g.,
{s:lower(s)}
is shorthand for
yield {s:lower(s)}
When operator names are omitted, search
has precedence over yield
, so
foo
is interpreted as a search for the string "foo" rather than a yield of
the implied record field named foo
.
Another common query pattern involves adding or mutating fields of records
where the input is presumed to be a sequence of records.
The put
operator provides this mechanism and the put
keyword is implied by the field assignment syntax :=
.
For example, the operation
put y:=2*x+1
can be expressed simply as
y:=2*x+1
When composing long-form queries that are shared via Zui or managed in GitHub, it is best practice to include all operator names in the Zed source text.
In summary, if no operator name is given, the implied operator is determined from the operator-less source text, in the order given, as follows:
- If the text can be interpreted as a search expression, then the operator is
search
. - If the text can be interpreted as a boolean expression, then the operator is
where
. - If the text can be interpreted as one or more field assignments, then the operator is
put
. - If the text can be interpreted as an aggregation, then the operator is
summarize
. - If the text can be interpreted as an expression, then the operator is
yield
. - Otherwise, the text causes a compile-time error.
When in doubt, you can always check what the compiler is doing under the hood
by running zq
with the -C
flag to print the parsed query in "canonical form", e.g.,
zq -C foo
zq -C 'is(<foo>)'
zq -C 'count()'
zq -C '{a:x+1,b:y-1}'
zq -C 'a:=x+1,b:=y-1'
produces
search foo
where is(<foo>)
summarize
count()
yield {a:x+1,b:y-1}
put a:=x+1,b:=y-1