Splunk® Enterprise

Search Reference

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Splunk SPL for SQL users

This is not a perfect mapping between SQL and Splunk Search Processing Language (SPL), but if you are familiar with SQL, this quick comparison might be helpful as a jump-start into using the search commands.

Concepts

The Splunk platform does not store data in a conventional database. Rather, it stores data in a distributed, non-relational, semi-structured database with an implicit time dimension. Relational databases require that all table columns be defined up-front and they do not automatically scale by just plugging in new hardware. However, there are analogues to many of the concepts in the database world.


Database Concept Splunk Concept Notes
SQL query Splunk search A Splunk search retrieves indexed data and can perform transforming and reporting operations. Results from one search can be "piped", or transferred, from command to command, to filter, modify, reorder, and group your results.
table/view search results Search results can be thought of as a database view, a dynamically generated table of rows, with columns.
index index All values and fields are indexed by Splunk software, so there is no need to manually add, update, drop, or even think about indexing columns. Everything can be quickly retrieved automatically.
row result/event A result in a Splunk search is a list of fields (i.e., column) values, corresponding to a table row. An event is a result that has a timestamp and raw text. Typically an event is a record from a log file, such as:

173.26.34.223 - - [01/Jul/2009:12:05:27 -0700] "GET /trade/app?action=logout HTTP/1.1" 200 2953

column field Fields are returned dynamically from a search, meaning that one search might return a set of fields, while another search might return another set. After teaching Splunk software how to extract more fields from the raw underlying data, the same search will return more fields than it previously did. Fields are not tied to a datatype.
database/schema index/app A Splunk index is a collection of data, somewhat like a database has a collection of tables. Domain knowledge of that data, how to extract it, what reports to run, etc, are stored in a Splunk application.

From SQL to Splunk SPL

SQL is designed to search relational database tables which are comprised of columns. SPL is designed to search events, which are comprised of fields. In SQL, you often see examples that use "mytable" and "mycolumn". In SPL, you will see examples that refer to "fields". In these examples, the "source" field is used as a proxy for "table". In Splunk software, "source" is the name of the file, stream, or other input from which a particular piece of data originates, for example /var/log/messages or UDP:514.

When translating from any language to another, often the translation is longer because of idioms in the original language. Some of the Splunk search examples shown below could be more concise and more efficient, but for parallelism and clarity, the SPL table and field names are kept the same as the SQL example.

  • SPL searches rarely need the FIELDS command to filter out columns because the user interface provides a more convenient method for filtering. The FIELDS command is used in the SPL examples for parallelism.
  • With SPL, you never have to use the AND operator in Boolean searches, because AND is implied between terms. However when you use the AND or OR operators, they must be specified in uppercase.
  • SPL commands do not need to be specified in uppercase. In the these SPL examples, the commands are specified in uppercase for easier identification and clarity.
  • Although some SPL commands loosely correspond to specific SQL commands as shown in the following table, your SPL searches might not produce the desired results if you "think in SQL." For this reason, avoid directly translating from SQL to SPL when you design your searches. See About the search language in the Search Manual for an overview of SPL.
SQL command SQL example Splunk SPL example
SELECT *
SELECT *
FROM mytable
source=mytable
WHERE
SELECT *
FROM mytable
WHERE mycolumn=5
source=mytable mycolumn=5
SELECT
SELECT mycolumn1, mycolumn2
FROM mytable
source=mytable	
| FIELDS mycolumn1, mycolumn2
AND/OR
SELECT *
FROM mytable
WHERE (mycolumn1="true" 
  OR mycolumn2="red") 
AND mycolumn3="blue"
source=mytable
AND (mycolumn1="true" 
  OR mycolumn2="red")
AND mycolumn3="blue"

Note: The AND operator is implied in SPL and does not need to be specified. For this example you could also use:

source=mytable
(mycolumn1="true" 
  OR mycolumn2="red")
mycolumn3="blue"
AS (alias)
SELECT mycolumn AS column_alias
FROM mytable
source=mytable
| RENAME mycolumn as column_alias
| FIELDS column_alias
BETWEEN
SELECT *
FROM mytable
WHERE mycolumn
BETWEEN 1 AND 5
source=mytable 
  mycolumn>=1 mycolumn<=5
GROUP BY
SELECT mycolumn, avg(mycolumn)
FROM mytable
WHERE mycolumn=value
GROUP BY mycolumn
source=mytable mycolumn=value
| STATS avg(mycolumn) BY mycolumn
| FIELDS mycolumn, avg(mycolumn)

Several commands use a by-clause to group information, including chart, rare, sort, stats, and timechart.

HAVING
SELECT mycolumn, avg(mycolumn)
FROM mytable
WHERE mycolumn=value
GROUP BY mycolumn
HAVING avg(mycolumn)=value
source=mytable mycolumn=value
| STATS avg(mycolumn) BY mycolumn
| SEARCH avg(mycolumn)=value
| FIELDS mycolumn, avg(mycolumn)
LIKE
SELECT *
FROM mytable
WHERE mycolumn LIKE "%some text%"
source=mytable 
  mycolumn="*some text*"

Note: The most common search in Splunk SPL is nearly impossible in SQL - to search all fields for a substring. The following SPL search returns all rows that contain "some text" anywhere:

source=mytable "some text" 
ORDER BY
SELECT *
FROM mytable
ORDER BY mycolumn desc
source=mytable
| SORT -mycolumn

In SPL you use a negative sign ( - ) in front of a field name to sort in descending order.

SELECT DISTINCT
SELECT DISTINCT 
  mycolumn1, mycolumn2
FROM mytable
source=mytable
| DEDUP mycolumn1, mycolumn2
| FIELDS mycolumn1, mycolumn2
SELECT TOP
SELECT TOP(5) 
mycolum1, 
mycolum2
FROM mytable1
WHERE mycolum3 = "bar"
ORDER BY mycolum1 mycolum2
Source=mytable1 mycolum3="bar"
| FIELDS mycolum1 mycolum2
| SORT mycolum1 mycolum2
| HEAD 5
INNER JOIN
SELECT *
FROM mytable1
INNER JOIN mytable2
ON mytable1.mycolumn= 
  mytable2.mycolumn
index=myIndex1 OR index=myIndex2
| stats values(*) AS * BY myField

Note: There are two other methods to join tables:

  • Use the lookup command to add fields from an external table:
... | LOOKUP myvaluelookup 
  mycolumn 
  OUTPUT myoutputcolumn
  • Use a subsearch:
source=mytable1
  [SEARCH source=mytable2 
    mycolumn2=myvalue
    | FIELDS mycolumn2]

If the columns that you want to join on have different names, use the rename command to rename one of the columns. For example, to rename the column in mytable2:

source=mytable1 
| JOIN type=inner mycolumn 
  [ SEARCH source=mytable2 
    | RENAME mycolumn2 
    AS mycolumn]

To rename the column in myindex1:

index=myIndex1 OR index=myIndex2
| rename myfield1 as myField
| stats values(*) AS * BY myField

You can rename a column regardless of whether you use the search command, a lookup, or a subsearch.

LEFT (OUTER) JOIN
SELECT *
FROM mytable1
LEFT JOIN mytable2
ON mytable1.mycolumn=
  mytable2.mycolumn
source=mytable1
| JOIN type=left mycolumn 
  [SEARCH source=mytable2]
SELECT INTO
SELECT *
INTO new_mytable IN mydb2
FROM old_mytable
source=old_mytable
| EVAL source=new_mytable
| COLLECT index=mydb2

Note: COLLECT is typically used to store expensively calculated fields back into your Splunk deployment so that future access is much faster. This current example is atypical but shown for comparison to the SQL command. The source will be renamed orig_source

TRUNCATE TABLE
TRUNCATE TABLE mytable
source=mytable
| DELETE
INSERT INTO
INSERT INTO mytable
VALUES (value1, value2, value3,....)
Note: see SELECT INTO. Individual records are not added via the search language, but can be added via the API if need be.
UNION
SELECT mycolumn
FROM mytable1
UNION
SELECT mycolumn FROM mytable2
source=mytable1
| APPEND 
  [SEARCH source=mytable2]
| DEDUP mycolumn
UNION ALL
SELECT *
FROM mytable1
UNION ALL
SELECT * FROM mytable2
source=mytable1
| APPEND 
  [SEARCH source=mytable2] 
DELETE
DELETE FROM mytable
WHERE mycolumn=5
source=mytable1 mycolumn=5
| DELETE
UPDATE
UPDATE mytable
SET column1=value, 
  column2=value,...
WHERE some_column=some_value
Note: There are a few things to think about when updating records in . First, you can just add the new values to your Splunk deployment (see INSERT INTO) and not worry about deleting the old values, because Splunk software always returns the most recent results first. Second, on retrieval, you can always de-duplicate the results to ensure only the latest values are used (see SELECT DISTINCT). Finally, you can actually delete the old records (see DELETE).

See also

Last modified on 01 September, 2023
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This documentation applies to the following versions of Splunk® Enterprise: 7.0.0, 7.0.2, 7.0.3, 7.0.4, 7.0.5, 7.0.6, 7.0.7, 7.0.8, 7.0.9, 7.0.10, 7.0.11, 7.0.13, 7.1.0, 7.1.1, 7.1.2, 7.1.3, 7.1.4, 7.1.5, 7.1.6, 7.1.7, 7.1.8, 7.1.9, 7.1.10, 7.2.0, 7.2.2, 7.2.3, 7.2.4, 7.2.5, 7.2.6, 7.2.7, 7.2.8, 7.2.9, 7.2.10, 7.3.0, 7.3.1, 7.3.2, 7.3.3, 7.3.4, 7.3.5, 7.3.6, 7.3.7, 7.3.8, 7.3.9, 8.0.0, 8.0.1, 8.0.2, 8.0.3, 8.0.5, 8.0.10, 7.2.1, 7.0.1, 8.0.4, 8.0.9, 8.1.0, 8.1.1, 8.1.2, 8.1.3, 8.1.4, 8.1.5, 8.1.6, 8.1.7, 8.1.8, 8.1.9, 8.1.10, 8.1.11, 8.1.12, 8.1.13, 8.1.14, 8.2.0, 8.2.1, 8.2.2, 8.2.3, 8.2.4, 8.2.5, 8.2.6, 8.2.7, 8.2.8, 8.2.9, 8.2.10, 8.2.11, 8.2.12, 9.0.0, 9.0.1, 9.0.2, 9.0.3, 9.0.4, 9.0.5, 9.0.6, 9.0.7, 9.0.8, 9.1.0, 9.1.1, 9.1.2, 9.1.3, 9.2.0, 8.0.6, 8.0.7, 8.0.8


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