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Pending Tasksedit
There are certain tasks that only the master can perform, such as creating a new index or moving shards around the cluster. Since a cluster can have only one master, only one node can ever process cluster-level metadata changes. For 99.9999% of the time, this is never a problem. The queue of metadata changes remains essentially zero.
In some rare clusters, the number of metadata changes occurs faster than the master can process them. This leads to a buildup of pending actions that are queued.
The pending-tasks
API will show you what (if any) cluster-level metadata changes
are pending in the queue:
GET _cluster/pending_tasks
Usually, the response will look like this:
{ "tasks": [] }
This means there are no pending tasks. If you have one of the rare clusters that bottlenecks on the master node, your pending task list may look like this:
{ "tasks": [ { "insert_order": 101, "priority": "URGENT", "source": "create-index [foo_9], cause [api]", "time_in_queue_millis": 86, "time_in_queue": "86ms" }, { "insert_order": 46, "priority": "HIGH", "source": "shard-started ([foo_2][1], node[tMTocMvQQgGCkj7QDHl3OA], [P], s[INITIALIZING]), reason [after recovery from gateway]", "time_in_queue_millis": 842, "time_in_queue": "842ms" }, { "insert_order": 45, "priority": "HIGH", "source": "shard-started ([foo_2][0], node[tMTocMvQQgGCkj7QDHl3OA], [P], s[INITIALIZING]), reason [after recovery from gateway]", "time_in_queue_millis": 858, "time_in_queue": "858ms" } ] }
You can see that tasks are assigned a priority (URGENT
is processed before HIGH
,
for example), the order it was inserted, how long the action has been queued and
what the action is trying to perform. In the preceding list, there is a create-index
action and two shard-started
actions pending.
- Elasticsearch - The Definitive Guide:
- Foreword
- Preface
- Getting Started
- You Know, for Search…
- Installing and Running Elasticsearch
- Talking to Elasticsearch
- Document Oriented
- Finding Your Feet
- Indexing Employee Documents
- Retrieving a Document
- Search Lite
- Search with Query DSL
- More-Complicated Searches
- Full-Text Search
- Phrase Search
- Highlighting Our Searches
- Analytics
- Tutorial Conclusion
- Distributed Nature
- Next Steps
- Life Inside a Cluster
- Data In, Data Out
- What Is a Document?
- Document Metadata
- Indexing a Document
- Retrieving a Document
- Checking Whether a Document Exists
- Updating a Whole Document
- Creating a New Document
- Deleting a Document
- Dealing with Conflicts
- Optimistic Concurrency Control
- Partial Updates to Documents
- Retrieving Multiple Documents
- Cheaper in Bulk
- Distributed Document Store
- Searching—The Basic Tools
- Mapping and Analysis
- Full-Body Search
- Sorting and Relevance
- Distributed Search Execution
- Index Management
- Inside a Shard
- You Know, for Search…
- Search in Depth
- Structured Search
- Full-Text Search
- Multifield Search
- Proximity Matching
- Partial Matching
- Controlling Relevance
- Theory Behind Relevance Scoring
- Lucene’s Practical Scoring Function
- Query-Time Boosting
- Manipulating Relevance with Query Structure
- Not Quite Not
- Ignoring TF/IDF
- function_score Query
- Boosting by Popularity
- Boosting Filtered Subsets
- Random Scoring
- The Closer, The Better
- Understanding the price Clause
- Scoring with Scripts
- Pluggable Similarity Algorithms
- Changing Similarities
- Relevance Tuning Is the Last 10%
- Dealing with Human Language
- Aggregations
- Geolocation
- Modeling Your Data
- Administration, Monitoring, and Deployment