一 read_only_allow_delete" : "true"
当我们在向某个索引添加一条数据的时候，可能（极少情况）会碰到下面的报错：
{
"error": {
"root_cause": [
{
"type": "cluster_block_exception",
"reason": "blocked by: [FORBIDDEN/12/index read-only / allow delete (api)];"
}
],
"type": "cluster_block_exception",
"reason": "blocked by: [FORBIDDEN/12/index read-only / allow delete (api)];"
},
"status": 403
}
上述报错是说索引现在的状态是只读模式（read-only），如果查看该索引此时的状态：
GET z1/_settings
# 结果如下
{
"z1" : {
"settings" : {
"index" : {
"number_of_shards" : "5",
"blocks" : {
"read_only_allow_delete" : "true"
},
"provided_name" : "z1",
"creation_date" : "1556204559161",
"number_of_replicas" : "1",
"uuid" : "3PEevS9xSm-r3tw54p0o9w",
"version" : {
"created" : "6050499"
}
}
}
}
}
可以看到"read_only_allow_delete" : "true"，说明此时无法插入数据，当然，我们也可以模拟出来这个错误：
PUT z1
{
"mappings": {
"doc": {
"properties": {
"title": {
"type":"text"
}
}
}
},
"settings": {
"index.blocks.read_only_allow_delete": true
}
}
PUT z1/doc/1
{
"title": "es真难学"
}
现在我们如果执行插入数据，就会报开始的错误。那么怎么解决呢？
- 清理磁盘，使占用率低于85%。
- 手动调整该项，具体参考官网
这里介绍一种，我们将该字段重新设置为：
PUT z1/_settings
{
"index.blocks.read_only_allow_delete": null
}
现在再查看该索引就正常了，也可以正常的插入数据和查询了。
二 illegal_argument_exception
有时候，在聚合中，我们会发现如下报错：
{
"error": {
"root_cause": [
{
"type": "illegal_argument_exception",
"reason": "Fielddata is disabled on text fields by default. Set fielddata=true on [age] in order to load fielddata in memory by uninverting the inverted index. Note that this can however use significant memory. Alternatively use a keyword field instead."
}
],
"type": "search_phase_execution_exception",
"reason": "all shards failed",
"phase": "query",
"grouped": true,
"failed_shards": [
{
"shard": 0,
"index": "z2",
"node": "NRwiP9PLRFCTJA7w3H9eqA",
"reason": {
"type": "illegal_argument_exception",
"reason": "Fielddata is disabled on text fields by default. Set fielddata=true on [age] in order to load fielddata in memory by uninverting the inverted index. Note that this can however use significant memory. Alternatively use a keyword field instead."
}
}
],
"caused_by": {
"type": "illegal_argument_exception",
"reason": "Fielddata is disabled on text fields by default. Set fielddata=true on [age] in order to load fielddata in memory by uninverting the inverted index. Note that this can however use significant memory. Alternatively use a keyword field instead.",
"caused_by": {
"type": "illegal_argument_exception",
"reason": "Fielddata is disabled on text fields by default. Set fielddata=true on [age] in order to load fielddata in memory by uninverting the inverted index. Note that this can however use significant memory. Alternatively use a keyword field instead."
}
}
},
"status": 400
}
这是怎么回事呢？是因为，聚合查询时，指定字段不能是text类型。比如下列示例：
PUT z2/doc/1
{
"age":"18"
}
PUT z2/doc/2
{
"age":20
}
GET z2/doc/_search
{
"query": {
"match_all": {}
},
"aggs": {
"my_sum": {
"sum": {
"field": "age"
}
}
}
}
当我们向elasticsearch中，添加一条数据时（此时，如果索引存在则直接新增或者更新文档，不存在则先创建索引），首先检查该age字段的映射类型。
如上示例中，我们添加第一篇文档时（z1索引不存在），elasticsearch会自动的创建索引，然后为age字段创建映射关系（es就猜此时age字段的值是什么类型，如果发现是text类型，那么存储该字段的映射类型就是text），此时age字段的值是text类型，所以，第二条插入数据，age的值也是text类型，而不是我们看到的long类型。我们可以查看一下该索引的mappings信息：
GET z2/_mapping
# mapping信息如下
{
"z2" : {
"mappings" : {
"doc" : {
"properties" : {
"age" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
}
}
}
}
}
}
上述返回结果发现，age类型是text。而该类型又不支持聚合，所以，就会报错了。解决办法就是：
- 如果选择动态创建一篇文档，映射关系取决于你添加的第一条文档的各字段都对应什么类型。而不是我们看到的那样，第一次是text，第二次不加引号，就是long类型了不是这样的。
- 如果嫌弃上面的解决办法麻烦，那就选择手动创建映射关系。首先指定好各字段对应什么类型。后续才不至于出错。
三 Result window is too large
很多时候，我们在查询文档时，一次查询结果很可能会有很多，而elasticsearch一次返回多少条结果，由size参数决定：
GET e2/doc/_search
{
"size": 100000,
"query": {
"match_all": {}
}
}
而默认是最多范围一万条，那么当我们的请求超过一万条时（比如有十万条），就会报：
Result window is too large, from + size must be less than or equal to: [10000] but was [100000]. See the scroll api for a more efficient way to request large data sets. This limit can be set by changing the [index.max_result_window] index level setting.
意思是一次请求返回的结果太大，可以另行参考 scroll API或者设置index.max_result_window参数手动调整size的最大默认值：
# kibana中设置
PUT e2/_settings
{
"index": {
"max_result_window": "100000"
}
}
# Python中设置
from elasticsearch import Elasticsearch
es = Elasticsearch()
es.indices.put_settings(index='e2', body={"index": {"max_result_window": 100000}})
如上例，我们手动调整索引e2的size参数最大默认值到十万，这时，一次查询结果只要不超过10万就都会一次返回。
注意，这个设置对于索引es的size参数是永久生效的。
以上就是Elasticsearch在应用中常见错误示例解析的详细内容，更多关于Elasticsearch错误示例解析的资料请关注阿兔在线工具其它相关文章！
