The search engine encountered the following error invalid or no response from elasticsearch перевод

Проблема с получением SSL сертефиката через Certbot. Detail: Invalid response from?

Ранее установил Certbot и успешно получил сертификат для одного из доменов. Возникла необходимость прикрутить еще один домен. Добавил домент в конфиг nginx, по http все ходит отлично, конфиг выглядит так:

При попытке получить сертификат для второго домена domain_name_2 получаю следующую ошибку:

Буду очень благодарен за помощь и идеи!

• Вопрос задан более двух лет назад
• 1629 просмотров

Средний 1 комментарий

Мне помогло или

или изменение timezone и времени на актуальные.
Или запись AAAA для IPv6 я удалил, чтобы искать в чём проблема

Тут вроде по русски написано
1. не смог положить файл domain_name_2/.well-known/acme-challenge/4UtNTakW9.
не хватило прав ли не смог сохранить.
2. вариант У вас в ДНС записях есть запимсь ААА — которая не поддерживается letsencrypt
3. ваши редиренкты отдают 302 вместо 200 как мы видем у васнет исключеня.

Теперь что касается каталога
то можно сделать так

и в моем случае ве эти файлики я прошу crtbot ложить в /usr/local/ispconfig/interface/acme/
получается как phpmyadmin дописав к любому сайту попадаешь в эту папку.
ДА и ваш домен не является секретным, вы его даже в директе прдвигаете, так что если вы его дадите будет проще разобраться

Источник

Invalid NEST response built from a unsuccessful #6148

Comments

shuangbaojun commented Mar 7, 2022 •

The sample code is as follows:

environment：
1、ElasticSearch 8.0.1
2、NEST 7.17.0
3、NET 6.0

ps：
Entering the account number and password through https://xx.xx.xxx.xxx:9200 can be accessed, but it cannot be accessed through the .net client, and the package error is as follows

The stack information is as follows:

Invalid NEST response built from a unsuccessful () low level call on PUT: /people/_doc/1

Audit trail of this API call:

• [1] ProductCheckOnStartup: Took: 00:00:00.6003806
• [2] ProductCheckFailure: Node: https://xx.xx.xxx.xxx:9200/ Took: 00:00:00.5720633

OriginalException: Elasticsearch.Net.ElasticsearchClientException: The client is unable to verify that the server is Elasticsearch due to an unsuccessful product check call. Some functionality may not be compatible if the server is running an unsupported product. Call: Status code unknown from: GET /

—> Elasticsearch.Net.PipelineException: The client is unable to verify that the server is Elasticsearch due to an unsuccessful product check call. Some functionality may not be compatible if the server is running an unsupported product.
—> System.Net.Http.HttpRequestException: The SSL connection could not be established, see inner exception.
—> System.Security.Authentication.AuthenticationException: The remote certificate is invalid according to the validation procedure: RemoteCertificateNameMismatch, RemoteCertificateChainErrors
at System.Net.Security.SslStream.SendAuthResetSignal(ProtocolToken message, ExceptionDispatchInfo exception)
at System.Net.Security.SslStream.CompleteHandshake(SslAuthenticationOptions sslAuthenticationOptions)
at System.Net.Security.SslStream.ForceAuthenticationAsync[TIOAdapter](TIOAdapter adapter, Boolean receiveFirst, Byte[] reAuthenticationData, Boolean isApm)
at System.Net.Http.ConnectHelper.EstablishSslConnectionAsync(SslClientAuthenticationOptions sslOptions, HttpRequestMessage request, Boolean async, Stream stream, CancellationToken cancellationToken)
— End of inner exception stack trace —
at System.Net.Http.ConnectHelper.EstablishSslConnectionAsync(SslClientAuthenticationOptions sslOptions, HttpRequestMessage request, Boolean async, Stream stream, CancellationToken cancellationToken)
at System.Net.Http.HttpConnectionPool.ConnectAsync(HttpRequestMessage request, Boolean async, CancellationToken cancellationToken)
at System.Net.Http.HttpConnectionPool.CreateHttp11ConnectionAsync(HttpRequestMessage request, Boolean async, CancellationToken cancellationToken)
at System.Net.Http.HttpConnectionPool.AddHttp11ConnectionAsync(HttpRequestMessage request)
at System.Threading.Tasks.TaskCompletionSourceWithCancellation 1.WaitWithCancellationAsync(CancellationToken cancellationToken) at System.Net.Http.HttpConnectionPool.GetHttp11ConnectionAsync(HttpRequestMessage request, Boolean async, CancellationToken cancellationToken) at System.Net.Http.HttpConnectionPool.SendWithVersionDetectionAndRetryAsync(HttpRequestMessage request, Boolean async, Boolean doRequestAuth, CancellationToken cancellationToken) at System.Net.Http.RedirectHandler.SendAsync(HttpRequestMessage request, Boolean async, CancellationToken cancellationToken) at System.Net.Http.HttpClient. g__Core|83_0(HttpRequestMessage request, HttpCompletionOption completionOption, CancellationTokenSource cts, Boolean disposeCts, CancellationTokenSource pendingRequestsCts, CancellationToken originalCancellationToken) at Elasticsearch.Net.HttpConnection.Request[TResponse](RequestData requestData) — End of inner exception stack trace — at Elasticsearch.Net.RequestPipeline.ThrowIfTransientProductCheckFailure() at Elasticsearch.Net.RequestPipeline.Ping(Node node) at Elasticsearch.Net.Transport 1.Ping(IRequestPipeline pipeline, Node node)
at Elasticsearch.Net.Transport`1.Request[TResponse](HttpMethod method, String path, PostData data, IRequestParameters requestParameters)
— End of inner exception stack trace —

Request:

Response:

The text was updated successfully, but these errors were encountered:

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Rebuild the Search server indexes for Bitbucket Server

Related content

Still need help?

The Atlassian Community is here for you.

Platform notice: Server and Data Center only. This article only applies to Atlassian products on the server and data center platforms .

For Bitbucket 7.20 and below, Elasticsearch was bundled. Starting with 7.21, OpenSearch is the bundled search server.

Reindex a specific repository:

If you need to reindex a specific repository, please see KB Reindex a specific repository for Code Search

Summary

When attempting a code search in Bitbucket, the «Search is currently unavailable» error is displayed in the user interface.

Other errors may be seen in the logs as a response to the search failure. In some cases, this can lead to high CPU for the bundled Search server Java process.

Environment

• Bitbucket 5.x, 6.x, and 7.x Server/DC

Diagnosis

Errors in Log Files

There are many different messages to show that the Search server index is corrupt, somehow. Some of the errors seen so far are outlined below:

Errors in the atlassian-bitbucket .log :

404 errors

A 404 status code indicates that the target resource could not be found.

503 errors

A 503 status code indicates that the target resource is unavailable.

400 errors

A 400 is a Bad Request and is typically associated with a misconfigured instance.

You are not permitted to access this resource

Errors may also appear in the bitbucket_search.log :

IndexxNotFoundException — The index does not exist.

Unable to find a field mapper for fieldFoundException — Incorrect mapping

Failed to load metadata — Unable to read the index data. A sign of corruption.

IndexShardRecoveryException — Unable to find or read the Search server shard files. A sign of corruption.

Check the content on the filesystem

List the search index files to see if the index has been corrupted or deleted, with one of the following two commands:

The tree command, if installed, lists contents of directories in a tree format. The -L argument displays the max depth of the tree.

If tree command is not available, you can use the following command:

The ls command lists directory content and the -R argument makes it recursive which lists the sub-directories contents.

The purpose of these commands is to list the whole structure of the data directory and its sub-directories and files. You can choose any of the commands above. These should return a large number of index files. Below is sample output after running the tree command:

The set of data retrieved by the commands above should be far larger than this. If this directory is empty or very few files exist, the index likely needs to be rebuilt.

Cause

• The search index in /shared/search/data has been deleted or corrupted and needs to be rebuilt.
• The repositories didn’t get fully indexed. Some possible reasons this might have happened are:

• • Search server issue
  • Temporary issue caused by high CPU utilization
  • Search server might have been down while the file was committed.

Solution

If there is an issue with the Indexing, you will see some of these errors in the atlassian-bitbucket.log or in the bitbucket_search.log. In case that happens, we recommend rebuilding the Search server index:

(Recommended) Resolution #1 — trigger a reindex

The Bitbucket Server REST API provides a way to restart indexing by making an HTTP request. This can be done when running a Bitbucket instance using the following curl command to make a POST to the /rest/indexing/latest/sync REST endpoint:

This will trigger a re-index of all repositories. Bitbucket will be available with all functionality other than search of unindexed portions of your code. The time it takes to index depends on how much indexable content you have. This will be the amount of code contained in files under 512 KB.

Resolution #2 — Delete the Index

This resolution requires downtime to stop the application since it tries to remove the content in the filesystem and fix the issue by attempting to rebuild the indexes after starting Bitbucket. If the «Resolution #1» option does not resolve the problem, perform the following steps:

For Bitbucket Server using bundled Search server:

1. Stop Bitbucket Server
2. Create a backup of /shared/search/data/nodes directory
3. Delete the contents of /shared/search/data/nodes directory
4. Start Bitbucket Server

For Bitbucket Server and Data Center using an external Search server instance:

1. Stop Bitbucket Server
2. Stop the Search server
3. Create a backup of SEARCH-SERVER_HOME> /data/local/nodes directory in your Search server
4. Delete the contents of SEARCH-SERVER_HOME> /data/local/nodes directory
5. Start the Search server
6. Start Bitbucket Server

Источник

The search engine encountered the following error: invalid or no response from Elasticsearch #202

Comments

TZubiri commented Jul 10, 2019 •

How to reproduce this error:

1- go to https://archive.org/

2- Use the lower search box to search for any url with a forward slash ( / ) after the TLD. For example site.com/page will fail, https://site.com should work without issue. Additionally book searches with this symbol will fail, like «Fahrenheit 9/11»

3- Receive error: » The search engine encountered the following error: invalid or no response from Elasticsearch »

How to workaround this issue:

The expected behaviour, from best user experience to worse:

1. Show me the crawled webpage https://web.archive.org/web/20190710055513/https://site.com/page
2. Show me the calendar of crawls https://web.archive.org/web/*/site.com/page
3. Show me a user-friendly error message, indicating one of the workarounds mentioned above, and suggesting the user strip symbols from his search query if they are looking for something other than a website.

I’m assuming it won’t come to 3, but I mention it just in case, as it is still preferrable to the actual behaviour.

Let me know if I can be of help.

The text was updated successfully, but these errors were encountered:

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Rebuild the Search server indexes for Bitbucket Server

Related content

Still need help?

The Atlassian Community is here for you.

Platform notice: Server and Data Center only. This article only applies to Atlassian products on the server and data center platforms .

For Bitbucket 7.20 and below, Elasticsearch was bundled. Starting with 7.21, OpenSearch is the bundled search server.

Reindex a specific repository:

If you need to reindex a specific repository, please see KB Reindex a specific repository for Code Search

Summary

When attempting a code search in Bitbucket, the «Search is currently unavailable» error is displayed in the user interface.

Other errors may be seen in the logs as a response to the search failure. In some cases, this can lead to high CPU for the bundled Search server Java process.

Environment

• Bitbucket 5.x, 6.x, and 7.x Server/DC

Diagnosis

Errors in Log Files

There are many different messages to show that the Search server index is corrupt, somehow. Some of the errors seen so far are outlined below:

Errors in the atlassian-bitbucket .log :

404 errors

A 404 status code indicates that the target resource could not be found.

503 errors

A 503 status code indicates that the target resource is unavailable.

400 errors

A 400 is a Bad Request and is typically associated with a misconfigured instance.

You are not permitted to access this resource

Errors may also appear in the bitbucket_search.log :

IndexxNotFoundException — The index does not exist.

Unable to find a field mapper for fieldFoundException — Incorrect mapping

Failed to load metadata — Unable to read the index data. A sign of corruption.

IndexShardRecoveryException — Unable to find or read the Search server shard files. A sign of corruption.

Check the content on the filesystem

List the search index files to see if the index has been corrupted or deleted, with one of the following two commands:

The tree command, if installed, lists contents of directories in a tree format. The -L argument displays the max depth of the tree.

If tree command is not available, you can use the following command:

The ls command lists directory content and the -R argument makes it recursive which lists the sub-directories contents.

The purpose of these commands is to list the whole structure of the data directory and its sub-directories and files. You can choose any of the commands above. These should return a large number of index files. Below is sample output after running the tree command:

The set of data retrieved by the commands above should be far larger than this. If this directory is empty or very few files exist, the index likely needs to be rebuilt.

Cause

• The search index in /shared/search/data has been deleted or corrupted and needs to be rebuilt.
• The repositories didn’t get fully indexed. Some possible reasons this might have happened are:

• • Search server issue
  • Temporary issue caused by high CPU utilization
  • Search server might have been down while the file was committed.

Solution

If there is an issue with the Indexing, you will see some of these errors in the atlassian-bitbucket.log or in the bitbucket_search.log. In case that happens, we recommend rebuilding the Search server index:

(Recommended) Resolution #1 — trigger a reindex

The Bitbucket Server REST API provides a way to restart indexing by making an HTTP request. This can be done when running a Bitbucket instance using the following curl command to make a POST to the /rest/indexing/latest/sync REST endpoint:

This will trigger a re-index of all repositories. Bitbucket will be available with all functionality other than search of unindexed portions of your code. The time it takes to index depends on how much indexable content you have. This will be the amount of code contained in files under 512 KB.

Resolution #2 — Delete the Index

This resolution requires downtime to stop the application since it tries to remove the content in the filesystem and fix the issue by attempting to rebuild the indexes after starting Bitbucket. If the «Resolution #1» option does not resolve the problem, perform the following steps:

For Bitbucket Server using bundled Search server:

1. Stop Bitbucket Server
2. Create a backup of /shared/search/data/nodes directory
3. Delete the contents of /shared/search/data/nodes directory
4. Start Bitbucket Server

For Bitbucket Server and Data Center using an external Search server instance:

1. Stop Bitbucket Server
2. Stop the Search server
3. Create a backup of SEARCH-SERVER_HOME> /data/local/nodes directory in your Search server
4. Delete the contents of SEARCH-SERVER_HOME> /data/local/nodes directory
5. Start the Search server
6. Start Bitbucket Server

Источник

LisaHJung/Part-6-Troubleshooting-Beginner-Level-Elasticsearch-Errors

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README.md

Beginner’s Crash Course to Elastic Stack Series

Part 6: Troubleshooting Beginner Level Elasticsearch Errors

Welcome to the Beginner’s Crash Course to Elastic Stack!

This repo contains all resources shared during Part 6: Troubleshooting Beginner-Level Elasticsearch Errors!

Throughout the series, we have learned about CRUD operations, fine tuning the relevance of your search, full text search, aggregations, and mapping.

As you continue your journey with Elasticsearch, you will inevitably encounter some common errors associated with the topics we have covered in the series.

Learn how to troubleshoot these pesky errors so you can get unstuck!

Table of Contents: Beginner’s Crash Course to Elastic Stack: This workshop is a part of the Beginner’s Crash Course to Elastic Stack series. Check out this table contents to access all the workshops in the series.

Instructions on how to access Elasticsearch and Kibana on Elastic Cloud

Instructions for downloading Elasticsearch and Kibana

Do you prefer learning by watching shorter videos? Check out this playlist to watch short clips of beginner’s crash course full length workshops. Season 2 clips will be uploaded here in the future!

YouTube Playlist of the Beginner’s Crash Course to Elastic Stack: Want to watch all the workshops in the series? Check out the YouTube playlist of the Beginner’s Crash Course to Elastic Stack!

Season 2 Topics Survey: I want to make the content more digestible for all of you!

Starting with season 2, I will discontinue holding live hour-long workshops and start uploading short clips(10 min or less) on YouTube Playlist of the Beginner’s Crash Course to Elastic Stack.

This series is created for YOU! Please let me know what you would like to learn in season 2 by submitting your preference in the survey.

I will create content on most requested topics along with other helpful topics for beginners!

Want To Troubleshoot Your Errors? Follow The Clues!

Whenever you perform an action with Elasticsearch and Kibana, Elasticsearch responds with an HTTP status and a response body.

The request below asks Elasticsearch to index a document and assign it an id of 1.

The HTTP status of 201-success indicates that the document has been successfully created. The response body indicates that the document with an assigned id of 1 has been created in the beginners_crash_course index.

As we work with Elasticsearch, we will inevitably encounter error messages like the one below.

When this happens, the HTTP status and the response body will provide valuable clues about why the request failed!

Here are some common errors that you may encounter as you work with Elasticsearch.

Unable to connect

The cluster may be down or it may be a network issue. Check the network status and cluster health to identify the problem.

Connection unexpectedly closed

The node may have died or it may be a network issue. Retry your request.

Errors with an HTTP status starting with 5 stems from internal server error in Elasticsearch. When you see this error, take a look at the Elasticsearch log and identify the problem.

Errors with an HTTP status starting with 4 stems from client errors. When you see this error, correct the request before retrying.

As beginners, we are still familiarizing ourselves with the rules and syntax required to communicate with Elasticsearch. Majority of the error messages we encouter are likely to have been caused by the mistakes we make while writing our requests(4XX errors).

To strengthen our understanding of the requests we have learned throughout the series, we will only focus on 4XX errors during this workshop.

Thought Process For Troubleshooting Errors

1. What number does the HTTP status start with(4XX? 5XX?)
2. What does the response say? Always read the full message!
3. Use the Elasticsearch documentation as your guide. Compare your request with the example from the documentation. Identify the mistake and make appropriate changes.

At times, you will encounter error messages that are not very helpful. We will go over a couple of these and see how we can troubleshoot these types of errors.

Trip Down Memory Lane

Throughout the series, we learned how to send requests related to the following topics:

1. CRUD operations
2. Queries
3. Aggregations
4. Mapping

We will revisit each topic and troubleshoot common errors you may encounter as you explore each topic.

Errors Associated With CRUD Operations

Error 1: 404 No such index[x]

In Part 1: Intro to Elasticsearch and Kibana, we learned how to perform CRUD operations. Let’s say we have sent the following request to retrieve a document with an id of 1 from the common_errors index.

Expected response from Elasticsearch:

Elasticsearch returns a 404-error along with the cause of the error in the response body. The HTTP status starts with a 4, meaning that there was a client error with the request sent.

When you look at the response body, Elasticsearch lists the reason(line 6) as «no such index [common_errors]».

The two possible explanations for this error are:

1. The index common_errors truly does not exist or was deleted
2. We do not have the correct index name

Cause of Error 1

In our example, the cause of the error is quite clear! We have not created an index called common_errors and we were trying to retrieve a document from an index that does not exist.

Let’s create an index called common_errors :

Expected response from Elasticsearch:

Elasticsearch returns a 200-success HTTP status acknowledging that the index common_errors has been successfully created.

Error 2: 405 Incorrect HTTP method for uri, allowed: [x]

Now that we have created the index common_errors , let’s index a document!

Suppose you have remembered that you could use the HTTP verb PUT to index a document and send the following request:

Expected response from Elasticsearch:

Elasticsearch returns a 405-error along with the cause of the error in the response body. This HTTP status starts with a 4, meaning that there was a client error with the request sent.

If you look at the response, Elasticsearch lists the reason as «Incorrect HTTP method for uri. and method: [PUT], allowed:[POST]».

Cause of Error 2

This error message suggests that we used the wrong HTTP verb to index this document.

You can use either PUT or POST HTTP verb to index a document. Each HTTP verb serves a different purpose and requires a different syntax.

We learned about the difference between the two verbs during Part 1: Intro to Elasticsearch and Kibana under the Index a document section.

When indexing a document, HTTP verb PUT or POST can be used.

The HTTP verb PUT is used when you want to assign a specific id to your document.

Let’s compare the syntax to the request we just sent:

You will see that our request uses the HTTP verb PUT but it does not include the document id we want to assign to this document.

If you add the id of the document to the request as seen below, you will see that the request is carried out without a hitch!

Correct example for PUT indexing request:

Expected response from Elasticsearch:

Elasticsearch returns a 201-success HTTP status acknowledging that document 1 has been successfully created.

The HTTP verb POST is used when you want Elasticsearch to autogenerate an id for the document.

If this is the option you wanted, you could fix the error message by replacing the verb PUT with POST and not including the document id after the document endpoint.

Correct example for POST indexing request:

Expected response from Elasticsearch:

Elasticsearch returns a 201-success HTTP status and autogenerates an id(line 4) for the document that was indexed.

Error 3: 400 Unexpected Character: was expecting a comma to separate Object entries at [Source: . ] line: x

Suppose you wanted to update document 1 by adding the fields «error» and «solution» as seen in the example.

Expected response from Elasticsearch:

Elasticsearch returns a 400-error along with the cause of the error in the response body. This HTTP error starts with a 4, meaning that there was a client error with the request sent.

Cause of Error 3

If you look at the response, Elasticsearch lists the error type(line 12) as «json_parse_exception» and the reason(line 13) as «. was expecting comma to separate Object entries at . line: 4]».

In Elasticsearch, if you have multiple fields(«errors» and «solution») in an object(«doc»), you must separate each field with a comma. The error message tells us that we need to add a comma between the fields «error» and «solution».

Add the comma as shown below and send the following request:

Expected response from Elasticsearch:

You will see that the document with an id of 1 has been successfully updated.

Errors Associated With Sending Queries

In parts 2 and 3, we learned how to send queries about news headlines in our index.

As a prerequisite part of these workshops, we added a news headlines dataset to an index we named as news_headlines .

We sent various queries to retrieve documents that match the criteria. Let’s go over common errors you may encounter while working with these queries.

Error 4: 400 [x] query does not support [y]

Suppose you want to use the range query to pull up news headlines published within a specific date range.

You have sent the following request:

Expected response from Elasticsearch:

Elasticsearch returns a 400-error along with the cause of the error in the response body. This HTTP status starts with a 4, meaning that there was a client error with the request sent.

If you look at the response, Elasticsearch lists the error type(line 5) as «parsing_exception» and the reason(line 6) as «[range] query does not support [date]».

This error message is misleading as the range query should be able to retrieve documents that contain terms within a provided range. It should not matter that you have requested to run a range query against the field «date».

Let’s check out the screenshots from the Elastic documentation on the range query to see what is going on.

Pay attention to the syntax of the range query line by line.

Screenshot from the documentation:

Compare this syntax to the request we have sent earlier:

Cause of Error 4

The culprit of this error is the range query syntax!

Our request is missing curly brackets around the inner fields(«gte» and «lte») of the field «date».

Let’s add the curly brackets as shown below and send the following request:

Expected response from Elasticsearch:

Elasticsearch returns a 200-success status and retrieves news headlines that were published between the specified date range.

Error 5: 400 Unexpected character. was expecting double-quote to start field name.

In Part 2, we learned about the multi_match query. This query allows you to search for the same search terms in multiple fields at one time.

Suppose you wanted to search for the phrase «party planning» in the fields headline and short_description as shown below:

Expected response from Elasticsearch:

Elasticsearch returns a 400-error along with the cause of the error in the response body. This HTTP status starts with a 4, meaning that something isn’t quite right with the request sent.

If you look at the response, Elasticsearch lists the error type(line 5) as «parsing_exception» and the reason(line 6) as «[multi_match] malformed query, expected [END_OBJECT] but found [FIELD_NAME]».

Cause of Error 5

This is a vague error message that does not really tell you what went wrong.

However, we do know that the error is coming from somewhere around line 10, which suggests that the error may have something to do with the «type» parameter(line 11).

When you check the opening and closing brackets from the outside in, you will realize that the «type» parameter is placed outside of the multi_match query.

Move the «type» parameter up a line and move the comma from line 10 to line 9 as shown below and send the request:

Expected response from Elasticsearch:

Elastcsearch returns a 200-success(red box) response.

All hits contain the phrase «party planning» in either the field «headline» or «short description» or both!

Error 6: 400 parsing_exception

When we search for something, we often ask a multi-faceted question. For example, you may want to retrieve entertainment news headlines published on «2018-04-12.»

This question actually requires sending multiple queries in one request:

1.A query that retrieves documents from the «ENTERTAINMENT» category 2.A query that retrieves documents that were published on «2018-04-12»

Let’s say you are most familiar with the match query so you write the following request:

Expected response from Elasticsearch:

Elasticsearch returns a 400-error along with the cause of the error in the response body. This HTTP status starts with a 4, meaning that something is off with the query syntax.

If you look at the response, Elasticsearch lists the error type(line 5) as «parsing_exception» and the reason(line 6) as «[match] query doesn’t support multiple fields, found [category] and [date]».

Cause of Error 6

Elasticsearch throws an error because a match query can query documents from only one field. Our request tried to query multiple fields using only one match query .

Bool Query

In Part 3, we learned how to combine multiple queries into one request by using the bool query .

With the bool query , you can combine multiple queries into one request and you can further specify boolean clauses to narrow down your search results.

This query offers four clauses that you can choose from:

You can mix and match any of these clauses to get the relevant search results you want.

In our use case, we have two queries:

1.A query that retrieves documents from the «ENTERTAINMENT» category 2.A query that retrieves documents that were published on «2018-04-12»

The news headlines we want could be filtered into a yes or no category:

Is the news headline from the «ENTERTAINMENT» category? yes or no Was the news headline published on «2018-04-12»? yes or no

When documents could be filtered into either a yes or no category, we can use the filter clause and include two match queries within it:

Expected response from Elastcsearch:

Elasticsearch returns a 200-success HTTP status and shows the top 10 hits whose «category» field contains the value «ENTERTAINMENT» and the «date» field contains the value of «2018-04-12».

Errors Associated With Aggregations and Mapping

Suppose you want to get the summary of categories that exist in our dataset. Since this requires summarizing your data, you decide to send the following aggregations request:

Expected response from Elasticsearch:

By default, Elasticsearch returns both top 10 search hits and aggregations results. Notice that the top 10 search hits take up lines 16-168.

Error 7: 400 Aggregation definition for [x], expected a [y].

Let’s say you are only interested in the aggregations results.

You remember that you can add a «size» parameter and set it equal to 0 to avoid fetching the hits.

You send the following request to accomplish this task:

Expected response from Elasticsearch:

Elasticsearch returns a 400-error along with the cause of the error in the response body. This HTTP status starts with a 4, meaning that there was a client error with the request sent.

If you look at the response, Elasticsearch lists the error type(line 5) as «parsing_exception» and the reason(line 6) as «Aggregation definition for [size starts with a [VALUE_NUMBER], expected a [START_OBJECT]».

Something is off with our aggregations request syntax. Let’s take a look at the screenshots from the Elastic documentation on aggregations and see what we missed.

Screenshot from the documentation: Pay close attention to the syntax of the aggregations request.

Cause of Error 7

This error is occurring because the «size» parameter was placed in a spot where Elasticsearch is expecting the name of the aggregations(«my-agg-name»).

If you scroll down to the Return only aggregation results section in the documentation, you will see that the «size» parameter is placed outside of the aggregations request as shown below.

Screenshot from the documentation:

Place the «size» parameter outside of the aggregations request and set it equal to 0 as shown below.

Send the following request:

Expected response from Elasticsearch:

As intended, Elasticsearch does not retrieve the top 10 hits(line 16).

You can see the aggregations results(an array of categories) without having to scroll through the hits.

Error 8: 400 Field [x] of type [y] is not supported for z type of aggregation

The next two errors(error 8 & 9) are related to the requests we have learned in Part 4: Aggregations and Part 5: Mapping workshops.

During these workshops, we have worked with e-commerce dataset.

In Part 4, we have added the e-commerce dataset to Elasticsearch and named the index ecommerce_original_data .

Then, we had to follow additional steps in Set up data within Elasticsearch section section in Part 4 repo.

Screenshot from Part 4 Repo:

To set up data within Elasticsearch, we implemented the following steps: We never covered why we had to go through these steps. It was all because of the the error message we are about to see next!

From this point on, imagine that you had just added the e-commerce dataset into the ecommerce_original_data index . We have not completed steps 1 and 2

In Part 4, we learned how to group data into buckets based on time interval. This type of aggregation request is called the date_histogram aggregation .

Suppose we wanted to group our data into 8 hour buckets and have sent the request below:

Expected response from Elasticsearch:

Elasticsearch returns a 400-error along with the cause of the error in the response body. This HTTP status starts with a 4, meaning that there was a client error with the request sent.

If you look at the response, Elasticsearch lists the error type(line 5) as «illegal_argument_exception» and the reason(line 6) as «Field [InvoiceDate] of type [keyword] is not supported for aggregation [date_histogram]».

This error is different from syntax error messages we have gone over thus far. It says that the field type «keyword» is not supported for the date_histogram aggregation , which suggests that this error may have something to do with the mapping.

Let’s check the mapping of the ecommerce_original_data index:

Expected response from Elasticsearch:

You will see that the field «InvoiceDate» is typed as «keyword».

Cause of Error 8

Screenshot from the documentation:

The first sentence gives us a valuable clue on why this error occurred!

The date_histogram aggregation cannot be performed on a field typed as «keyword».

To perform a date_histogram aggregation on the «InvoiceDate» field, the «InvoiceDate» field must be mapped as field type «date».

But the mapping for the field «date» already exists. What are we going to do?!

Remember, you cannot change the mapping of the existing field!

The only way you can accomplish this is to: Step 1: Create a new index with the desired mapping Step 2: Reindex data from the original index to the new one Step 3: Send the date_histogram aggregation request to the new index

In Part 4, this is why we carried out steps 1 and 2!

Step 1: Create a new index(ecommerce_data) with the following mapping

Side note about error associated with the _meta field

If you were following the steps from Setting up data within Elasticsearch section from Part 4, you probably have enountered the following error:

This was due to a typo in the request where I forgot to include an underscore before meta in line 4.

The _meta field is a space used to include any notes that you want as a reference. It can be tips about common bug fixes or info about your app that you want to include.

The _meta field is completely optional. For our use case, it is not necessary so I have removed the _meta field from Part 4 repo since this issue came to my attention.

Sincere apologies to anybody who has encountered that error while following along and thank you to @radhakrishnaakamat for catching the error!!

Side note about adding the format of the «InvoiceDate» field

Let’s look at the date format of the field «InvoiceDate»:

Expected response from Elasticsearch:

The format of the InvoiceDate is «M/d/yyyy H:m».

By default, Elasticsearch is configured to recognize iso8601 date format(ex. 2021-07-16T17:12:56.123Z).

If the date format in your dataset differs from the iso8601 format, Elasticsearch will not recognize it and throw an error.

In order to prevent this from happening, we specify the date format of the «InvoiceDate» field(«format»: «M/d/yyyy H:m») within the mapping.

The symbols used in date format was formed using this documentation.

We have covered a LOT! Let’s do a recap on why we are carrying out these steps in the first place.

In Part 4, we added the e-commerce dataset to the ecommerce_original_data index where the field «InvoiceDate» was dynamically typed as «keyword».

When we tried to run a date_histogram aggregation on the field «InvoiceDate», Elasticsearch threw an error saying that it can only perform the date_histogram aggregation on a field typed as «date».

Since we could not change the mapping of an existing field «InvoiceDate», we had to carry out step 1 where we created a new index called ecommerce_data with the desired mapping for the field «InvoiceDate».

Step 2: Reindex the data from original index(«source») to the one you just created(«dest»).

At this point, we have a new index called ecommerce_data with the desired mapping. However, there is no data in this index.

To correct that, we will send the following request to reindex the data from the ecommerce_original_data index to the ecommerce_data index:

Expected response from Elasticsearch:

Elasticsearch successfully reindexes the e-commerce dataset from the ecommerce_original_data index to the ecommerce_data index.

Step 3: Send the date_histogram aggregations request to the new index(ecommerce_data).

Now that the data has been reindexed to the new index, let’s send the date_histogram aggregation request we sent earlier.

The following is almost identical to the original request except that the index name has been changed to the new index( ecommerce_data ).

Expected response from Elasticsearch:

Elasticsearch returns a 200-success response. It divides the dataset into 8 hour buckets and returns them in the response.

Error 9: 400 Found two aggregation type definitions in [x]: y and z

One of the cool things about Elasticsearch is that you can build any combination of aggregations to answer more complex questions.

For example, let’s say we want to get the daily revenue and the number of unique customers per day.

This requires grouping data into daily buckets.

Within each bucket, we calculate the daily revenue and the number of unique customers per day.

Let’s say we wrote the following request to accomplish this task:

Expected response from Elasticsearch:

Elasticsearch returns a 400-error along with the cause of the error in the response body. This HTTP error starts with a 4, meaning that there was a client error with the request sent.

Cause of Error 9

This error is occurring because the structure of the aggregations request is incorrect.

In order to accomplish our goals, we first group data into daily buckets. Within each bucket, we calculate the daily revenue and the unique number of customers per day.

Therefore, our request contains an aggregation(pink brackets) within an aggregation(blue brackets).

The following demonstrates the correct aggregations request structure. Note the sub-aggregations that encloses the «daily_revenue» and the «number_of_unique_customers_per_day»:

Expected response from Elasticsearch:

Elasticsearch returns a 200-success HTTP status.

It groups the dataset into daily buckets. Within each bucket, the number of unique customers per day as well as the daily revenue are calculated.

Источник

View Post [edit]

Poster:	rwalk333	Date:	Oct 23, 2018 10:14am
Forum:	forums	Subject:	Elasticsearch Error

I’ve noticed the following error message when running an advanced search and downloading to CSV. Looks like one of the Elasticsearch nodes may be in an unhealthy state, as I can reproduce this consistently.

to reproduce this specifically, run an advanced search for «Collections:usfederalcourts», set a huge number of requested results and export to CSV.

«`
INTERNAL_ERROR: invalid or no response from Elasticsearch

forensics: {«request_url»:»http://es-lb:9200/_search/scroll»,»status_code»:»500″,»raw_reply»:»{«error»:{«root_cause»:[{«type»:»illegal_state_exception»,»reason»:»node [Mhrq3kzLTJyldXoWMd360A] is not available»},{«type»:»illegal_state_exception»,»reason»:»node [_nO_KVIMSk6ECiNHnKdv8g] is not available»},{«type»:»illegal_state_exception»,»reason»:»node [d2LSTukCTqecAcFTdjR6oQ] is not available»},{«type»:»illegal_state_exception»,»reason»:»node [hOvYB9KGSf2jMkMwlEVpPg] is not available»}],»type»:»search_phase_execution_exception»,»reason»:»all shards failed»,»phase»:»query»,»grouped»:true,»failed_shards»:[{«shard»:-1,»index»:null,»reason»:{«type»:»illegal_state_exception»,»reason»:»node [Mhrq3kzLTJyldXoWMd360A] is not available»}},{«shard»:-1,»index»:null,»reason»:{«type»:»illegal_state_exception»,»reason»:»node [_nO_KVIMSk6ECiNHnKdv8g] is not available»}},{«shard»:-1,»index»:null,»reason»:{«type»:»illegal_state_exception»,»reason»:»node [d2LSTukCTqecAcFTdjR6oQ] is not available»}},{«shard»:-1,»index»:null,»reason»:{«type»:»illegal_state_exception»,»reason»:»node [hOvYB9KGSf2jMkMwlEVpPg] is not available»}}]},»status»:500}»,»decoded_reply»:{«error»:{«root_cause»:[{«type»:»illegal_state_exception»,»reason»:»node [Mhrq3kzLTJyldXoWMd360A] is not available»},{«type»:»illegal_state_exception»,»reason»:»node [_nO_KVIMSk6ECiNHnKdv8g] is not available»},{«type»:»illegal_state_exception»,»reason»:»node [d2LSTukCTqecAcFTdjR6oQ] is not available»},{«type»:»illegal_state_exception»,»reason»:»node [hOvYB9KGSf2jMkMwlEVpPg] is not available»}],»type»:»search_phase_execution_exception»,»reason»:»all shards failed»,»phase»:»query»,»grouped»:true,»failed_shards»:[{«shard»:-1,»index»:null,»reason»:{«type»:»illegal_state_exception»,»reason»:»node [Mhrq3kzLTJyldXoWMd360A] is not available»}},{«shard»:-1,»index»:null,»reason»:{«type»:»illegal_state_exception»,»reason»:»node [_nO_KVIMSk6ECiNHnKdv8g] is not available»}},{«shard»:-1,»index»:null,»reason»:{«type»:»illegal_state_exception»,»reason»:»node [d2LSTukCTqecAcFTdjR6oQ] is not available»}},{«shard»:-1,»index»:null,»reason»:{«type»:»illegal_state_exception»,»reason»:»node [hOvYB9KGSf2jMkMwlEVpPg] is not available»}}]},»status»:500},»message»:»check for decoded endpoint_reply»}
«`

Reply [edit]

Poster:	Aaron Ximm	Date:	Oct 24, 2018 11:21am
Forum:	forums	Subject:	Re: Elasticsearch Error

Hi,

Thanks for this report! I added this error reporting to advancedsearch earlier this month to try to get more visibility into (previously, just as occurring, but silent) failures, which are unique to retrieval of [very] large results sets.

Reporting like this is invaluable, thank you! (Fwiw we see this same error doing other internal searches for large result sets; I am trying to get to the root cause.)

Best regards,
Aaron

Reply [edit]

Poster:	wondererJf	Date:	Feb 12, 2022 5:35am
Forum:	forums	Subject:	Re: Elasticsearch Error

Aaron is there a way to contact you directly ? if so pleSe do let me know how asap.ty

Reply [edit]

Poster:	Larry Wake	Date:	Jan 6, 2019 11:51am
Forum:	forums	Subject:	Re: Elasticsearch Error

I’m getting the same error today as Maximara reported:

The search engine encountered the following error: invalid or no response from Elasticsearch

when searching for the URL

http://wine.appellationamerica.com/wine-region/Fair-Play.html

This post was modified by Larry Wake on 2019-01-06 19:50:31

This post was modified by Larry Wake on 2019-01-06 19:51:49

Reply [edit]

Poster:	Jeff Kaplan	Date:	Jan 6, 2019 4:56pm
Forum:	forums	Subject:	Re: Elasticsearch Error

that is the wayback machine. a completely different search engine.

Reply [edit]

Poster:	Maximara	Date:	Dec 20, 2018 8:40am
Forum:	forums	Subject:	Re: Elasticsearch Error

I got «The search engine encountered the following error: invalid or no response from Elasticsearch» simply by trying to search for archives of https://rpg.rem.uz/

Summary

When attempting a code search in Bitbucket, the «Search is currently unavailable» error is displayed in the user interface.

Other errors may be seen in the logs as a response to the search failure. In some cases, this can lead to high CPU for the bundled Search server Java process.

Environment

• Bitbucket 5.x, 6.x, and 7.x Server/DC

Diagnosis

Errors in Log Files

There are many different messages to show that the Search server index is corrupt, somehow. Some of the errors seen so far are outlined below:

Errors in the atlassian-bitbucket.log:

404 errors

Unexpected response code from Elasticsearch: 404

com.atlassian.bitbucket.search.indexer.exceptions.IndexException: Unexpected error occurred when requesting index state document (id=43) the HTTP Status code is: 404

A 404 status code indicates that the target resource could not be found.

503 errors

ERROR [http-nio-7990-exec-16] X182486 <session id> <username> <ip address> "POST /rest/search/latest/search HTTP/1.1" c.a.b.s.internal.rest.SearchResource Unexpected response code from Elasticsearch: 503

A 503 status code indicates that the target resource is unavailable.

400 errors

ERROR [http-nio-7990-exec-2746] user *1U2QK8x795x992313x2 c6fz54 10.10.10.5,10.10.10.13 "POST /rest/search/latest/search HTTP/1.1" c.a.b.i.s.search.rest.SearchResource Unexpected response code from Elasticsearch: 400

A 400 is a Bad Request and is typically associated with a misconfigured instance.

You are not permitted to access this resource

ERROR [https-jsse-nio-8443-exec-26] n0200293 <session id> <username> <ip address> "POST /rest/search/latest/search HTTP/1.1" c.a.b.i.s.search.rest.SearchResource Failed to process search request 'RestSearchRequest{entities={code=PagingInfo{start=0, limit=0}}, limits=Limits{primary=25, secondary=10}, query='<search keyword>'}' - error: You are not permitted to access this resource

Errors may also appear in the bitbucket_search.log:

IndexxNotFoundException — The index does not exist.

[bitbucket-search] IndexNotFoundException[no such index]

Unable to find a field mapper for fieldFoundException — Incorrect mapping

Caused by: ElasticsearchException[Unable to find a field mapper for field [quickSearchProjectName.length]. No 'missing' value defined.]

Unable to read the index data. A sign of corruption.

[2020-12-02T10:03:52,001][ERROR][o.e.b.Bootstrap          ] [bitbucket_bundled]Exception
org.elasticsearch.ElasticsearchException: failed to load metadata
...
Failed to load metadata Caused by: java.io.IOException: failed to find metadata for existing index bitbucket-index-state [location: IAdbCfIHT4yFBHhlsSk5VQ, generation: 5]

IndexShardRecoveryException — Unable to find or read the Search server shard files. A sign of corruption.

[2016-11-23 16:10:27,080][WARN ][indices.cluster          ] [bitbucket_bundled] [[bitbucket-search-v1][3]] marking and sending shard failed due to [failed recovery]
[bitbucket-search-v1][[bitbucket-search-v1][3]] IndexShardRecoveryException[failed to recovery from gateway]; nested: EngineCreationFailureException[failed to create engine]; nested: NoSuchFileException[/var/atlassian/application-data/bitbucket/shared/search/data/bitbucket_search/nodes/0/indices/bitbucket-search-v1/3/translog/translog-7.tlog];
        at org.elasticsearch.index.shard.StoreRecoveryService.recoverFromStore(StoreRecoveryService.java:250)
...
Caused by: [bitbucket-search-v1][[bitbucket-search-v1][3]] EngineCreationFailureException[failed to create engine]; nested: NoSuchFileException[/var/atlassian/application-data/bitbucket/shared/search/data/bitbucket_search/nodes/0/indices/bitbucket-search-v1/3/translog/translog-7.tlog];
        at org.elasticsearch.index.engine.InternalEngine.< int>(InternalEngine.java:155)
...
Caused by: java.nio.file.NoSuchFileException: /var/atlassian/application-data/bitbucket/shared/search/data/bitbucket_search/nodes/0/indices/bitbucket-search-v1/3/translog/translog-7.tlog
        at sun.nio.fs.UnixException.translateToIOException(UnixException.java:86)
... 

Check the content on the filesystem

List the search index files to see if the index has been corrupted or deleted, with one of the following two commands:

tree -L 8 <bitbucket-home>/shared/search/data

 The tree command, if installed, lists contents of directories in a tree format. The -L argument displays the max depth of the tree.

If tree command is not available, you can use the following command:

ls -R <bitbucket-home>/shared/search/data

 The ls command lists directory content and the -R argument makes it recursive which lists the sub-directories contents.

The purpose of these commands is to list the whole structure of the data directory and its sub-directories and files. You can choose any of the commands above. These should return a large number of index files. Below is sample output after running the tree command:

...
_0_1.liv  _1.si   _4.si              _e_Lucene50_0.tim  _e.si   _g.si
_0.cfe    _2.cfe  _e.fdt             _e_Lucene50_0.tip  _f.cfe  segments_1
_0.cfs    _2.cfs  _e.fdx             _e_Lucene54_0.dvd  _f.cfs  write.lock
_0.si     _2.si   _e.fnm             _e_Lucene54_0.dvm  _f.si
_1.cfe    _4.cfe  _e_Lucene50_0.doc  _e.nvd             _g.cfe
_1.cfs    _4.cfs  _e_Lucene50_0.pos  _e.nvm             _g.cfs
...

The set of data retrieved by the commands above should be far larger than this. If this directory is empty or very few files exist, the index likely needs to be rebuilt.

Cause

• The search index in <bitbucket-home>/shared/search/data has been deleted or corrupted and needs to be rebuilt.
• The repositories didn’t get fully indexed. Some possible reasons this might have happened are:

• • Search server issue
  • Temporary issue caused by high CPU utilization
  • Search server might have been down while the file was committed.

Solution

If there is an issue with the Indexing, you will see some of these errors in the atlassian-bitbucket.log or in the bitbucket_search.log. In case that happens, we recommend rebuilding the Search server index:

(Recommended) Resolution #1 — trigger a reindex

The Bitbucket Server REST API provides a way to restart indexing by making an HTTP request. This can be done when running a Bitbucket instance using the following curl command to make a POST to the /rest/indexing/latest/sync REST endpoint:

curl -u <admin-user> -X POST -H 'Content-Type: application/json' -H 'Accept: application/json' <bitbucket-url>/rest/indexing/latest/sync

This will trigger a re-index of all repositories. Bitbucket will be available with all functionality other than search of unindexed portions of your code.  The time it takes to index depends on how much indexable content you have. This will be the amount of code contained in files under 512 KB.

Resolution #2 — Delete the Index

This resolution requires downtime to stop the application since it tries to remove the content in the filesystem and fix the issue by attempting to rebuild the indexes after starting Bitbucket. If the «Resolution #1» option does not resolve the problem, perform the following steps:

For Bitbucket Server using bundled Search server:

1. Stop Bitbucket Server
2. Create a backup of <Bitbucket-home>/shared/search/data/nodes directory
3. Delete the contents of <Bitbucket-home>/shared/search/data/nodes directory
4. Start Bitbucket Server

For Bitbucket Server and Data Center using an external Search server instance:

1. Stop Bitbucket Server
2. Stop the Search server
3. Create a backup of <SEARCH-SERVER_HOME>/data/local/nodes directory in your Search server
4. Delete the contents of <SEARCH-SERVER_HOME>/data/local/nodes directory
5. Start the Search server
6. Start Bitbucket Server