I am trying to parse log using ELK stack. following is my sample log
2015-12-11 12:05:24+0530 [process] INFO: process 0.24.5 started
I am using the following grok
grok{
match => {"message" => "(?m)%{TIMESTAMP_ISO8601:processdate}\s+\[%{WORD:name}\]\s+%{LOGLEVEL:loglevel}"}
}
and my elastic search mapping is
{
"properties": {
"processdate":{
"type": "date",
"format" : "yyyy-MM-dd HH:mm:ss+SSSS"
},
"name":{"type" : "string"},
"loglevel":{"type" : "string"},
}
}
But while loading into Elastic search i am getting below error,
"error"=>{"type"=>"mapper_parsing_exception", "reason"=>"failed to parse [processdate]", "caused_by"=>{"type"=>"illegal_argument_exception", "reason"=>"Invalid format: \"2015-12-11 12:05:39+0530\" is malformed at \" 12:05:39+0530\""}}}}, :level=>:warn}
How to modify it to a proper data format? I have added the proper date format in elastic search.
Update: localhost:9200/log
{"log":{"aliases":{},"mappings":{"filelog":{"properties":{"processdate":{"type":"date","format":"yyyy-MM-dd' 'HH:mm:ssZ"},"loglevel":{"type":"string"},"name":{"type":"string"}}}},"settings":{"index":{"creation_date":"1458218007417","number_of_shards":"5","number_of_replicas":"1","uuid":"_7ffuioZS7eGBbFCDMk7cw","version":{"created":"2020099"}}},"warmers":{}}}
The error you're getting means that your date format is wrong. Fix your date format like this, i.e. use Z (timezone) at the end instead of +SSSS (fraction of seconds):
{
"properties": {
"processdate":{
"type": "date",
"format" : "yyyy-MM-dd HH:mm:ssZ"
},
"name":{"type" : "string"},
"loglevel":{"type" : "string"}
}
}
Also, according to our earlier exchange, your elasticsearch output plugin is missing the document_type setting and should be configured like this instead in order to make use of your custom filelog mapping type (otherwise the default logs type is being used and your custom mapping type is not kicking in):
output {
elasticsearch {
hosts => ["172.16.2.204:9200"]
index => "log"
document_type => "filelog"
}
}
Related
I want to create a date histogram with opensearch dashboards. The time format of my data is YYYY-MM-DD HH:mm:ss.SSS, which I have set under Stack Management > Advanced Settings > Date Format. I get an error like this:
Under Discover, I can sort by "date", as it is of type "float". My field "timestamp", by which I would like to sort, is of type "string", and I cannot change this via the API:
{"error":{"root_cause":[{"type":"illegal_argument_exception","reason":"mapper [timestamp] cannot be changed from type [text] to [date]"}],"type":"illegal_argument_exception","reason":"mapper [timestamp] cannot be changed from type [text] to [date]"},"status":400}
I'm stuck, can someone please help?
To use a field for date histogram aggregation, the field type should be a date.
Unfortunately, it's not possible to change the field type from Kibana => Stack management.
Here is some solution for your case:
Use Histogram aggregation
Set the field type and re-index the data
Here are the steps for the second option.
#Check the mapping old_index = your existing index name
GET old_index
#Put the new mapping before reindexing
PUT new_index
{
"mappings": {
"properties": {
"timestamp": {
"type": "date",
"format": ["YYYY-MM-DD HH:mm:ss.SSS"]
}
}
}
}
#reindex the data
POST _reindex?wait_for_completion=false
{
"source": {
"index": "old_index"
},
"dest": {
"index": "new_index"
}
}
I am trying to populate dashboard in kibana with Elasticsearch data on date fields .
I have log file with dates and i find that i don't have #timestamp in it.
Here is mapping :
PUT test2
{
"settings": {
"index.mapping.ignore_malformed": true
},
"mappings": {
"my_type": {
"properties": {
"Size": {"type": "integer","ignore_malformed": true },
"Copy Size": {"type": "integer","ignore_malformed": true }
"Email Sent Time": {"type": "date"},
"Creation Time": {"type": "date"},
"Modification Time": {"type": "date"}
}
}
}
}
How to add default timestamp? To create area chart in kibana.
Once upon a time, Elasticsearch used to support adding default timestamps automatically to all documents you put in an index. The mapping was something like this when creating your index:
"mappings" : {
"_default_":{
"_timestamp" : {
"enabled" : true,
"store" : true
}
}
}
However, as you can see at this link, it was deprecated by version 5.x. Today, it is recommended to populate a regular date field with the current timestamp on application side.
I am using elasticsearch 5.x and Filebeat and want to know if there is a way of parsing date(timestamp) directly in filebeat (don't want to use logstash). I am using json.keys_under_root: true and it works great, but the problem is that timestamp (on us) is recognised as string. All of the other fields were automatically recognised as correct types only this one isn't.
How can I map it as date?
You can use Filebeat with the ES Ingest Node feature to parse your timestamp field and apply the value to the #timestamp field.
You would setup a simple pipeline in Elasticsearch that applies a date to incoming events.
PUT _ingest/pipeline/my-pipeline
{
"description" : "parse timestamp and update #timestamp",
"processors" : [
{
"date" : {
"field" : "timestamp",
"target_field" : "#timestamp"
}
},
{
"remove": {
"field": "timestamp"
}
}
],
"on_failure": [
{
"set": {
"field": "error.message",
"value": "{{ _ingest.on_failure_message }}"
}
}
]
}
Then in Filebeat configure the elasticsearch output to push data to your new pipeline.
output.elasticsearch:
hosts: ["http://localhost:9200"]
pipeline: my-pipeline
I have already parsed a log file using logstash and put it into elasticsearch. I have a field called IP and it is mapped as a string now. I want to convert the existing mapping in elasticsearch to geoip without running logstash again. I have few million records in elasticsearch with this field. I want to convert the mapping of IP from string to geoip in all the records.
I'm afraid you still have to use Logstash for this because geoip is a Logstash filter and Elasticsearch doesn't have access to the GeoIP database by itself.
Fear not, though, you won't need to re-run Logstash on the raw log lines, you can simply re-index your ES documents using an elasticsearch input plugin and an elasticsearch output plugin and by tacking the geoip filter inbetween in order to transform the IP field into the geoip one.
Since you can't modify the mapping of your current IP field from string to geo_point, we need to make sure your index is ready to ingest GeoIP data. First check with the following command if your index already contains a geoip field in your mapping (which would have been created by Logstash using its predefined standard logstash-* template).
curl -XGET localhost:9200/logstash-xyz/_mapping
If you see a geoip field in the output of the above command, then you're good to go. Otherwise, we first need to create the geoip field with the type geo_point:
curl -XPUT localhost:9200/logstash-xyz/_mapping/your_type -d '{
"your_type": {
"properties": {
"geoip": {
"type": "object",
"dynamic": true,
"properties": {
"ip": {
"type": "ip",
"doc_values": true
},
"location": {
"type": "geo_point",
"doc_values": true
},
"latitude": {
"type": "float",
"doc_values": true
},
"longitude": {
"type": "float",
"doc_values": true
}
}
}
}
}
}'
Now your mapping is ready to receive GeoIP data. So, next we create a Logstash configuration file called geoip.conf that looks like this:
input {
elasticsearch {
hosts => "localhost:9200"
index => "logstash-xyz"
}
}
filter {
mutate {
remove_field => [ "#version", "#timestamp" ]
}
geoip {
source => "IP" <--- the field containing the IP string
}
}
output {
elasticsearch {
host => "localhost"
port => 9200
protocol => "http"
manage_template => false
index => "logstash-xyz"
document_id => "%{id}"
workers => 1
}
}
And then after setting the correct values (host + index), you can run this with bin/logstash -f geoip.conf. After running this, your documents should contain a new field called geoip with the GeoIP information.
Going forth, I suggest you directly add the geoip filter to your normal logstash configuration.
I've been playing around with getting a tab delimited file into Elasticsearch using the CSV filter in Logstash. Getting the data in was actually incredibly easy, but I'm having trouble getting the field types to come in right when I look at the data in Kibana. Dates and integers continue to come in as strings, so I can't plot by date or do any analysis functions on integers (sum, mean, etc).
I'm also having trouble getting the .raw version of the fields to populate. For example, in device I have data like "HTC One", but when if I do a pie chart in Kibana, it'll show up as two separate groupings "HTC" and "One". When I try to chart device.raw instead, it comes up as a missing field. From what I've read, it seems like Logstash should automatically create a raw version of each string field, but that doesn't seem to be happening.
I've been sifting through the documentation, google and stack, but haven't found a solution. Any ideas appreciated! Thanks.
Config file:
#logstash.conf
input {
file {
path => "file.txt"
type => "event"
start_position => "beginning"
sincedb_path => "/dev/null"
}
}
filter {
csv {
columns => ["userid","date","distance","device"]
separator => " "
}
}
output {
elasticsearch {
action => "index"
host => "localhost"
port => "9200"
protocol => "http"
index => "userid"
workers => 2
template => template.json
}
#stdout {
# codec => rubydebug
#}
}
Here's the template file:
#template.json:
{
"template": "event",
"settings" : {
"number_of_shards" : 1,
"number_of_replicas" : 0,
"index" : {
"query" : { "default_field" : "userid" }
}
},
"mappings": {
"_default_": {
"_all": { "enabled": false },
"_source": { "compress": true },
"dynamic_templates": [
{
"string_template" : {
"match" : "*",
"mapping": { "type": "string", "index": "not_analyzed" },
"match_mapping_type" : "string"
}
}
],
"properties" : {
"date" : { "type" : "date", "format": "yyyy-MM-dd HH:mm:ss"},
"device" : { "type" : "string", "fields": {"raw": {"type": "string","index": "not_analyzed"}}},
"distance" : { "type" : "integer"}
}
}
}
Figured it out - the template name IS the index. So the "template" : "event" line should have been "template" : "userid"
I found another (easier) way to specify the type of the fields. You can use logstash's mutate filter to change the type of a field. Simply add the following filter after your csv filter to your logstash config
mutate {
convert => [ "fieldname", "integer" ]
}
For details check out the logstash docs - mutate convert