I recently started working in a company that uses Elasticsearch. While most of its concepts are somewhat similar to relational databases and I am able to understand them, I still don't quite get the concept of aliases.
I did not find any such question here and the information provided on the Elasticsearch website did not help much either.
Can someone explain what aliases are for and ideally include an example of a situation where they are needed?
aliases are like soft links or shortcuts to actual indexes
the advantage is to be able to have an alias pointing to index1a while building or re-indexing on index2b and the moment of swapping them is atomic thanks to the alias, to which all code should point
Renaming an alias is a simple remove then add operation within the same API. This operation is atomic, no need to worry about a short period of time where the alias does not point to an index:
[EDIT] as pointed out #wholevinski aliases have other functionalities like:
Multiple indices can be specified for an action ...
all the info is in the page you have linked
[EDIT2] more on why the need/benefit of the atomicity
the key being "zero downtime" https://en.wikipedia.org/wiki/Zero_unscheduled_downtime or https://en.wikipedia.org/wiki/High_availability
https://www.elastic.co/guide/en/elasticsearch/guide/current/index-aliases.html
We will talk more about the other uses for aliases later in the book. For now we will explain how to use them to switch from an old index to a new index with zero downtime.
#arhak covered the topic pretty well.
One use case that (at least) made me understand the value of indices was the need to remove out-of-date documents and more specifically when using time-based-indices.
For example, you need to keep the logs of an application for at least one year. You decide to use time-based-indices, meaning you save into indices with the following format: 2018-02-logs, 2018-03-logs etc.. In order to be able to search in every index you create the following alias:
POST /_aliases
{
"actions": [{
"add": {
"alias": "current-logs", "indices": [ "2018-02-logs","2018-03-logs" ]
}
}]
}
And query like:
GET /current-logs/_search
Another advantage is that you can delete the out-of-date values very easily:
POST /_aliases
{
"actions": [
{ "remove": { "alias": "current-logs", "index": "logs_2018-01" }}
]
}
and DELETE /logs_2018-01
Aliases are basically created to group a set of indices and make them accessible regarless the name they have. Is a pointer to a set of indices. You can also apply a query/condition to all of these indices. It is very useful when performing queries or creating dashboards over the same group of indices all the time. In addition, if in the future you change the name of the indices that are part of an alias, the end users will not notice that change since it is for transparent for them and you will only update the pointer.
Related
I come across the following phrase and I am under impression that a valid 6.x query with type might give an error. I am using the cluster ES 7.10
Note that in 7.0, _doc is a permanent part of the path, and represents
the endpoint name rather than the document type.
But, to my surprise, I am able to run the following query. Does it mean _doc is NOT permanent part of the path? In specific, what kind of queries I need to modify when I am moving from 6.x to 7.x
PUT ecommercesite/product/1
{
"product_name": "Men High Performance Fleece Jacket",
"description": "Best Value. All season fleece jacket",
"unit_price": 79.99,
"reviews": 250,
"release_date": "2016-08-16"
}
And only the 6.x query, I am not able to run on 7.10. I got an error with respect to type.
GET ecommercesite/product/_mapping
The PUT requests currently (end of 2020) just throws a warning but will fail in 8.x.
For now, you could start replacing product with _doc:
PUT ecommercesite/product/1 --> PUT ecommercesite/_doc/1
GET ecommercesite/product/_mapping --> GET ecommercesite/_doc/_mapping?include_type_name
but it'd be best to ditch the types completely and adhere to the standards:
important: instead of PUT ecommercesite/1 either keep using PUT ecommercesite/_doc/1 or use PUT /ecommercesite/_create/1 (docs here)
GET ecommercesite/_mapping (docs here)
no significant changes in GET ecommercesite/_search
It's often useful to have the _id as a part of the document. In fact it's advised here: https://www.elastic.co/guide/en/elasticsearch/reference/current/mapping-id-field.html
But if you do not know the _id prior to document creation, how would you duplicate the _id during indexing? The only way I can think of doing it is using a pipeline but is there a simpler way?
Edit: according to answer below even a pipeline cannot achieve this.
Ingest pipelines (current version 7.9.2) cannot access the _id if the _id is generated. There is a note in the documentation saying:
If you automatically generate document IDs, you cannot use the {{_id}} value in an ingest processor. Elasticsearch assigns auto-generated _id values after ingest.
The copy_to feature also don't work for _id when auto generated. This Information is a little bit hidden here https://github.com/elastic/elasticsearch/issues/6730#issuecomment-103142553
Queries with script_fieldsusing doc['_id'].value is deprecated too.
It seems to me that this is what many of us are looking for, for different reasons, but there is no solution at least I am aware of.
The case is obviously complete different for self generated document id.
In case someone still looking for Solution to this issue
You can do a reindexing with script tag and use the context object to get grab of the _id and matched it the ID in the POCO
POST /_reindex?wait_for_completion=false
{
"source": {
"index": "data.dataitems",
"query": {
"match_all": {}
}
},
"dest": {
"index": "data.dataitems_new_index_with_id"
},"script": {
"source": "ctx._source.id = ctx._id"
}
}
I am trying to get a list which shows me all sources ES is receiving messages from. I am pretty new with this topic and trying to get deeper into it. I am searching basically for a solution to see the total amount of sources sending logs to my central logging solution and in best case also provided my a list with the source names.
Does anyone have an idea how to get such information querying Elasticsearch?
Yes, this is possible, though the solution depends on how your data looks.
Users typically index data in Elasticsearch so that it contains more than just the raw log lines. This is done automatically if you're using Filebeat. Otherwise, you'd do something (add a field using Logstash, rely on a host field in syslog, etc) to ensure you have a field that contains your "source" identifier:
{
"message": "my super valuable logline",
"source": "my_kinda_awesome_app"
}
given ^^ you can identify all sources (and record counts!) with a terms aggregation like:
{
"aggs": {
"my_sources": {
"terms": { "field": "source" }
}
}
}
Kibana makes this all easier since you don't need to know/write ES queries and can do stuff visually.
I'm trying to write logs to an Elasticsearch index from a Kubernetes cluster. Fluent-bit is being used to read stdout and it enriches the logs with metadata including pod labels. A simplified example log object is
{
"log": "This is a log message.",
"kubernetes": {
"labels": {
"app": "application-1"
}
}
}
The problem is that a few other applications deployed to the cluster have labels of the following format:
{
"log": "This is another log message.",
"kubernetes": {
"labels": {
"app.kubernetes.io/name": "application-2"
}
}
}
These applications are installed via Helm charts and the newer ones are following the label and selector conventions as laid out here. The naming convention for labels and selectors was updated in Dec 2018, seen here, and not all charts have been updated to reflect this.
The end result of this is that depending on which type of label format makes it into an Elastic index first, trying to send the other type in will throw a mapping exception. If I create a new empty index and send in the namespaced label first, attempting to log the simple app label will throw this exception:
object mapping for [kubernetes.labels.app] tried to parse field [kubernetes.labels.app] as object, but found a concrete value
The opposite situation, posting the namespaced label second, results in this exception:
Could not dynamically add mapping for field [kubernetes.labels.app.kubernetes.io/name]. Existing mapping for [kubernetes.labels.app] must be of type object but found [text].
What I suspect is happening is that Elasticsearch sees the periods in the field name as JSON dot notation and is trying to flesh it out as an object. I was able to find this PR from 2015 which explicitly disallows periods in field names however it seems to have been reversed in 2016 with this PR. There is also this multi-year thread from 2015-2017 discussing this issue but I was unable to find anything recent involving the latest versions.
My current thoughts on moving forward is to standardize the Helm charts we are using to have all of the labels use the same convention. This seems like a band-aid on the underlying issue though which is that I feel like I'm missing something obvious in the configuration of Elasticsearch and dynamic field mappings.
Any help here would be appreciated.
I opted to use the Logstash mutate filter with the rename option as described here:
https://www.elastic.co/guide/en/logstash/current/plugins-filters-mutate.html#plugins-filters-mutate-rename
The end result looked something like this:
filter {
mutate {
'[kubernetes][labels][app]' => '[kubernetes][labels][app.kubernetes.io/name]'
'[kubernetes][labels][chart]' => '[kubernetes][labels][helm.sh/chart]'
}
}
Although personally I've never encountered the exact same issue, I had similar problems when I indexed some test data and afterwards changed the structure of the document that should have been indexed (especially when "unflattening" data structures).
Your interpretation of the error message is correct. When you first index the document
{
"log": "This is another log message.",
"kubernetes": {
"labels": {
"app.kubernetes.io/name": "application-2"
}
}
}
Elasticsearch will recognize the app as an object/structure due to dynamic mapping.
When you then try to index the document
{
"log": "This is a log message.",
"kubernetes": {
"labels": {
"app": "application-1"
}
}
}
the previously, dynamically created mapping defined the field app as an object with sub-fields but elasticsearch encounters a concrete value, namely "application-1".
I suggest that you setup an index template to define the correct mappings. For the 'outdated' logging-versions I suggest to pre-process the particular documents either through an elasticsearch ingest-pipeline or with e.g. Logstash to get the documents in the correct format.
Hope that helps.
Using NEST, I need to be able to order a terms aggregation with multiple criteria (requires ElasticSearch 1.5 or later). For example:
"order": [{"avg_rank": "desc"}, {"avg_score": "desc"}]
This is working great using the raw JSON that I created to verify I was getting the expected behavior. Now, in trying to translate that over to code using the NEST library, I'm not seeing how that would be accomplished.
The OrderDescending() method has only one implementation that takes a string for the key. I need a C# "params" type method that can take a list of OrderDescending() and\or OrderAscending() elements.
Is there a way to do this in NEST that I'm overlooking?
Is there a way in NEST to work around this where I can inject a little raw JSON where I need it?
FWIW, I've been using the "fluent" style to create my queries.
EDIT:
I see that, using "object initializer" syntax, I could manually create the dictionary and add my criteria elements. Problem is, I have large amounts of code written in "fluent" syntax. So,
Is there a way to use an "object initializer" object and convert it to a "fluent" descriptor? In this case, a TermsAggregator to a TermsAggregationDescriptor?
EDIT 2:
I should have mentioned originally that I tried .OrderDescending("avg_rank").OrderDescending("avg_score") already. That simply took that last one in the chain. In looking at the code, I can see why. Each call to OrderDescending blindly news up the dictionary instead of checking to see if one was already newed up and adding a new key to the dictionary if it already exists.
Based on this, I believe this is a bug for which I have entered a report here:
OrderDescending and OrderAscending cannot be chained for multi-criteria ordering
EDIT 3:
I appreciate all the answers (some of which are getting deleted) because they're helping drive this along and are responsible for these edits. I should also have mentioned originally that I discovered that:
"order": { "avg_rank": "desc", "avg_score": "desc" }
does not work. I don't know why for sure but ES will only use the last one in that case. It has be a list of dictionaries as shown in my example above at the top. I've verified that correctly sub-orders the aggregation on the second element. So, the underlying object cannot be typed as a simple dictionary. I've also added this information to the bug report I created (as noted in EDIT 2).
If you're using the fluent syntax you can just chain the sorts together.
Sample:
var esClient = ninjectKernel.Get<IElasticClient>();
var query = esClient.Search<RedemptionES>(s=> s
.SortAscending(a=>a.Date)
.SortDescending(d=>d.Input.User.Name)
);
Response:
{
"sort": [
{
"#timestamp": {
"order": "asc"
}
},
{
"input.user.name": {
"order": "desc"
}
}
]
}
Martijn Laarman of the NEST team was very responsive and kind enough to provide a work around for the bug I reported in EDIT 2 of the description above. The fix can be found in the comments of that same bug report: Work around for NEST library multi-criteria aggregation ordering.
Note that he provided a work around for both object initializer and fluent syntaxes (the one I needed).