問題
一次在使用Elasticsearch來存儲(chǔ)數(shù)據(jù)的時(shí)候,前端在把數(shù)據(jù)保存成功后,調(diào)用查詢列表的接口來刷新列表時(shí),發(fā)現(xiàn)有時(shí)能刷新出新保存的數(shù)據(jù),有時(shí)候又不能,修改和刪除數(shù)據(jù)也發(fā)現(xiàn)有類似現(xiàn)象。但是再次刷新頁面的時(shí)候又可以查詢到新操作的數(shù)據(jù)。
后面發(fā)現(xiàn)這個(gè)問題是Elasticsearch本身在操作數(shù)據(jù)后有一定的延遲性導(dǎo)致。Elasticsearch默認(rèn)情況下在寫入數(shù)據(jù)后,是要等1s后才能被查詢到。
因?yàn)镋lasticsearch中每次索引refresh會(huì)產(chǎn)生一個(gè)新的 lucene 段,這會(huì)導(dǎo)致頻繁的 segment merge 行為,對系統(tǒng) CPU 和 IO 占用都比較高。
解決方法1
需要修改ElasticSearch的刷新策略
org.elasticsearch.action.support.WriteRequest.RefreshPolicy 中定義了三種刷新策略:
enum RefreshPolicy implements Writeable {
/**
* Don't refresh after this request. The default.
*/
NONE("false"),
/**
* Force a refresh as part of this request. This refresh policy does not scale for high indexing or search throughput but is useful
* to present a consistent view to for indices with very low traffic. And it is wonderful for tests!
*/
IMMEDIATE("true"),
/**
* Leave this request open until a refresh has made the contents of this request visible to search. This refresh policy is
* compatible with high indexing and search throughput but it causes the request to wait to reply until a refresh occurs.
*/
WAIT_UNTIL("wait_for");
IMMEDIATE
- 請求向ElasticSearch提交了數(shù)據(jù),立即刷新數(shù)據(jù)后,再結(jié)束請求。
- 優(yōu)點(diǎn):操作延時(shí)短、實(shí)時(shí)性高
- 缺點(diǎn):資源消耗高
WAIT_UNTIL
- 請求向ElasticSearch提交了數(shù)據(jù),等待數(shù)據(jù)完成刷新(默認(rèn)為1s),然后再結(jié)束請求。
- 優(yōu)點(diǎn):實(shí)時(shí)性高、操作延時(shí)長
- 缺點(diǎn):資源消耗低
NONE (默認(rèn)策略)
- 請求向ElasticSearch提交了數(shù)據(jù),不等待數(shù)據(jù)完成刷新,直接結(jié)束請求。
- 優(yōu)點(diǎn):操作延時(shí)短、資源消耗低
- 缺點(diǎn):實(shí)時(shí)性低
org.elasticsearch.action.support.WriteRequestBuilder中的setRefreshPolicy方法,默認(rèn)為設(shè)置為RefreshPolicy#NONE
/**
* Should this request trigger a refresh ({@linkplain RefreshPolicy#IMMEDIATE}), wait for a refresh (
* {@linkplain RefreshPolicy#WAIT_UNTIL}), or proceed ignore refreshes entirely ({@linkplain RefreshPolicy#NONE}, the default).
*/
@SuppressWarnings("unchecked")
default B setRefreshPolicy(RefreshPolicy refreshPolicy) {
request().setRefreshPolicy(refreshPolicy);
return (B) this;
}
代碼中設(shè)置 setRefreshPolicy
setRefreshPolicy(WriteRequest.RefreshPolicy.IMMEDIATE) 設(shè)置為立即刷新,即可解決不能立即查詢到數(shù)據(jù)的問題。
// 刪除 設(shè)置為WriteRequest.RefreshPolicy.IMMEDIATE 立即刷新
DeleteRequestBuilder deleteRequestBuilder = transportClient.prepareDelete(INDEX, TYPE, id).setRefreshPolicy(WriteRequest.RefreshPolicy.IMMEDIATE);
// 新增
IndexRequestBuilder indexRequestBuilder = transportClient.prepareIndex(INDEX, TYPE, id).setRefreshPolicy(WriteRequest.RefreshPolicy.IMMEDIATE);
// 更新
UpdateRequestBuilder updateRequestBuilder = transportClient.prepareUpdate(INDEX, TYPE,id).setRefreshPolicy(WriteRequest.RefreshPolicy.IMMEDIATE);
// 批量
BulkRequestBuilder bulkRequestBuilder = transportClient.prepareBulk().setRefreshPolicy(WriteRequest.RefreshPolicy.IMMEDIATE);
支持的接口:
- 刪除:DeleteRequestBuilder
- 新增:IndexRequestBuilder
- 更新:UpdateRequestBuilder
- 批量:BulkRequestBuilder
解決方法2
在查詢結(jié)果前使用sleep來暫停一段時(shí)間再執(zhí)行查詢操作,這樣可以不改變ElasticSearch的刷新策略。
當(dāng)業(yè)務(wù)需要頻繁的操作修改數(shù)據(jù)的情況下,設(shè)置刷新策略為立即刷新的話可能會(huì)造成性能問題。
我們可以使用sleep的方式不去修改默認(rèn)的刷新策略。
當(dāng)我們在執(zhí)行新增、修改、刪除、批量操作的時(shí)候,在這些操作中設(shè)置一把鎖,過期時(shí)間為1s(這個(gè)時(shí)間剛好是刷新策略的默認(rèn)時(shí)間),在查詢數(shù)據(jù)時(shí)我們需要先去檢查是否有鎖,如果有鎖存在我們就等待500ms后再執(zhí)行查詢操作。這樣基本上又可以保證不改刷新策略,也可以保存查詢的實(shí)時(shí)性。
/**
* 在新增、修改、刪除、批量操作的時(shí)候設(shè)置鎖
*/
private void setLock() {
redisService.setWithExpire(getEsParentUpdateKey(), UPDATING_MSG, 1);
}
/**
* 查詢r(jià)edis中的鎖是否存在,如果有鎖,將暫停500毫秒,再執(zhí)行查詢操作
*/
private void waitMe() {
Object lock = redisService.get(getEsParentUpdateKey());
if (lock != null) {
try {
//為了得到ES更新后的數(shù)據(jù),暫停500s
TimeUnit.MICROSECONDS.sleep(500);
} catch (InterruptedException e) {
e.printStackTrace();
}
}
}