Skip to content

Commit

Permalink
[DOCS] Adds web session details example to painless transform examples (
Browse files Browse the repository at this point in the history 
#57942)
  • Loading branch information
@szabosteve
szabosteve committed Jun 15, 2020
1 parent eef0154 commit 5057b57
Showing 1 changed file with 175 additions and 2 deletions.
177 changes: 175 additions & 2 deletions docs/reference/transform/painless-examples.asciidoc
View file
Original file line number Diff line number Diff line change
Expand Up @@ -16,6 +16,7 @@ more about the Painless scripting language in the
* <<painless-bucket-script>>
* <<painless-count-http>>
* <<painless-compare>>
* <<painless-web-session>>

NOTE: While the context of the following examples is the {transform} use case,
the Painless scripts in the snippets below can be used in other {es} search
Expand Down Expand Up @@ -296,7 +297,7 @@ The example uses the {kib} sample web logs dataset.

[source,console]
--------------------------------------------------
PUT _data_frame/transforms/data_log
PUT _transform/data_log
{
"source": {
"index": "kibana_sample_data_logs"
Expand Down Expand Up @@ -470,4 +471,176 @@ want to pass the full source object from one phase to the next.
<7> The `reduce_script` checks if the size of the indices are equal. If they are
not equal, than it reports back a `count_mismatch`. Then it iterates through all
the values of the two indices and compare them. If the values are equal, then it
returns a `match`, otherwise returns a `mismatch`.
returns a `match`, otherwise returns a `mismatch`.

[discrete]
[[painless-web-session]]
==== Getting web session details by using scripted metric aggregation

This example shows how to derive multiple features from a single transaction.
Let's take a look on the example source document from the data:

.Source document
[%collapsible%open]
=====
[source,js]
--------------------------------------------------
{
"_index":"apache-sessions",
"_type":"_doc",
"_id":"KvzSeGoB4bgw0KGbE3wP",
"_score":1.0,
"_source":{
"@timestamp":1484053499256,
"apache":{
"access":{
"sessionid":"571604f2b2b0c7b346dc685eeb0e2306774a63c2",
"url":"http://www.leroymerlin.fr/v3/search/search.do?keyword=Carrelage%20salle%20de%20bain",
"path":"/v3/search/search.do",
"query":"keyword=Carrelage%20salle%20de%20bain",
"referrer":"http://www.leroymerlin.fr/v3/p/produits/carrelage-parquet-sol-souple/carrelage-sol-et-mur/decor-listel-et-accessoires-carrelage-mural-l1308217717?resultOffset=0&resultLimit=51&resultListShape=MOSAIC&priceStyle=SALEUNIT_PRICE",
"user_agent":{
"original":"Mobile Safari 10.0 Mac OS X (iPad) Apple Inc.",
"os_name":"Mac OS X (iPad)"
},
"remote_ip":"0337b1fa-5ed4-af81-9ef4-0ec53be0f45d",
"geoip":{
"country_iso_code":"FR",
"location":{
"lat":48.86,
"lon":2.35
}
},
"response_code":200,
"method":"GET"
}
}
}
}
...
--------------------------------------------------
// NOTCONSOLE
=====


By using the `sessionid` as a group-by field, you are able to enumerate events
through the session and get more details of the session by using scripted metric
aggregation.

[source,js]
--------------------------------------------------
POST _transform/_preview
{
"source": {
"index": "apache-sessions"
},
"pivot": {
"group_by": {
"sessionid": { <1>
"terms": {
"field": "apache.access.sessionid"
}
}
},
"aggregations": { <2>
"distinct_paths": {
"cardinality": {
"field": "apache.access.path"
}
},
"num_pages_viewed": {
"value_count": {
"field": "apache.access.url"
}
},
"session_details": {
"scripted_metric": {
"init_script": "state.docs = []", <3>
"map_script": """ <4>
Map span = [
'@timestamp':doc['@timestamp'].value,
'url':doc['apache.access.url'].value,
'referrer':doc['apache.access.referrer'].value
];
state.docs.add(span)
""",
"combine_script": "return state.docs;", <5>
"reduce_script": """ <6>
def all_docs = [];
for (s in states) {
for (span in s) {
all_docs.add(span);
}
}
all_docs.sort((HashMap o1, HashMap o2)->o1['@timestamp'].millis.compareTo(o2['@timestamp'].millis));
def size = all_docs.size();
def min_time = all_docs[0]['@timestamp'];
def max_time = all_docs[size-1]['@timestamp'];
def duration = max_time.millis - min_time.millis;
def entry_page = all_docs[0]['url'];
def exit_path = all_docs[size-1]['url'];
def first_referrer = all_docs[0]['referrer'];
def ret = new HashMap();
ret['first_time'] = min_time;
ret['last_time'] = max_time;
ret['duration'] = duration;
ret['entry_page'] = entry_page;
ret['exit_path'] = exit_path;
ret['first_referrer'] = first_referrer;
return ret;
"""
}
}
}
}
}
--------------------------------------------------
// NOTCONSOLE

<1> The data is grouped by `sessionid`.
<2> The aggregations counts the number of paths and enumerate the viewed pages
during the session.
<3> The `init_script` creates an array type `doc` in the `state` object.
<4> The `map_script` defines a `span` array with a timestamp, a URL, and a
referrer value which are based on the corresponding values of the document, then
adds the value of the `span` array to the `doc` object.
<5> The `combine_script` returns `state.docs` from each shard.
<6> The `reduce_script` defines various objects like `min_time`, `max_time`, and
`duration` based on the document fields, then declares a `ret` object, and
copies the source document by using `new HashMap ()`. Next, the script defines
`first_time`, `last_time`, `duration` and other fields inside the `ret` object
based on the corresponding object defined earlier, finally returns `ret`.

The API call results in a similar response:

[source,js]
--------------------------------------------------
{
"num_pages_viewed" : 2.0,
"session_details" : {
"duration" : 131374,
"first_referrer" : "https://www.bing.com/",
"entry_page" : "http://www.leroymerlin.fr/v3/p/produits/materiaux-menuiserie/porte-coulissante-porte-interieure-escalier-et-rambarde/barriere-de-securite-l1308218463",
"first_time" : "2017-01-10T21:22:52.982Z",
"last_time" : "2017-01-10T21:25:04.356Z",
"exit_path" : "http://www.leroymerlin.fr/v3/p/produits/materiaux-menuiserie/porte-coulissante-porte-interieure-escalier-et-rambarde/barriere-de-securite-l1308218463?__result-wrapper?pageTemplate=Famille%2FMat%C3%A9riaux+et+menuiserie&resultOffset=0&resultLimit=50&resultListShape=PLAIN&nomenclatureId=17942&priceStyle=SALEUNIT_PRICE&fcr=1&*4294718806=4294718806&*14072=14072&*4294718593=4294718593&*17942=17942"
},
"distinct_paths" : 1.0,
"sessionid" : "000046f8154a80fd89849369c984b8cc9d795814"
},
{
"num_pages_viewed" : 10.0,
"session_details" : {
"duration" : 343112,
"first_referrer" : "https://www.google.fr/",
"entry_page" : "http://www.leroymerlin.fr/",
"first_time" : "2017-01-10T16:57:39.937Z",
"last_time" : "2017-01-10T17:03:23.049Z",
"exit_path" : "http://www.leroymerlin.fr/v3/p/produits/porte-de-douche-coulissante-adena-e168578"
},
"distinct_paths" : 8.0,
"sessionid" : "000087e825da1d87a332b8f15fa76116c7467da6"
}
...
--------------------------------------------------
// NOTCONSOLE

0 comments on commit 5057b57

Please sign in to comment.