數據庫優化的三個例子
1）沒有加索引
2）查詢語句導致索引用不上
3）過多的連接數據庫
例子1：
在一個大型的計算中原來每天要花費半小時才能完成，對計算的過程進行仔細的分析，發現下面的語句花費了很長時間
select sum(order_qty - delivery_qty - reduce_confirm_qty - lost_qty ) qty from circle_ordering where sku = ‘" . $sku . "‘ AND submit_status = 5 AND order_type = ‘AIR‘
通過explain 這條語句，仔細分析數據庫才知道並沒有相關的索引作用在這條查詢語句上，這樣導致了這條sql是全表查詢。於是對這三列（sku, submit_status, order_type）新建索引. 重新執行後，整個程序只用了10份鐘就完成了。
例子2:
select a.ebay_id, b.ebay_id as ebay_subid, from_unixtime(a.ebay_paidtime) as ebay_paidtime, a.ebay_account, a.ebay_countryname, c.store_name as warehouse, a.ebay_carrier, b.sku, b.ebay_amount, a.ebay_currency, b.ebay_itemprice, b.shipingfee, ((b.ebay_itemprice*b.ebay_amount)+b.shipingfee) as total_amount, ebay_postcode, b.item_promotion_discount_amount, b.ship_promotion_discount_amount from ebay_order a left join ebay_orderdetail b on(a.ebay_ordersn=b.ebay_ordersn) left join ebay_store c on (a.ebay_warehouse = c.id) where a.ebay_combine !=1 and (a.resend_org_ebay_id=0 or a.resend_org_ebay_id is null) and b.ebay_amount >0 and a.ebay_warehouse !=‘‘ and a.ebay_user=‘manwei‘ and ( a.ebay_paidtime between UNIX_TIMESTAMP(‘".$astart."‘) and UNIX_TIMESTAMP(‘".$aend."‘) or (a.ebay_paidtime not between UNIX_TIMESTAMP(‘".$astart_p."‘) and UNIX_TIMESTAMP(‘".$aend_p."‘) and a.shippedtime between UNIX_TIMESTAMP(‘".$astart_p."‘) and UNIX_TIMESTAMP(‘".$aend_p."‘)) "; if($last_ebay_id!=‘‘) $data .= " or a.ebay_id >=‘".$last_ebay_id."‘"; $data .= ") order by a.ebay_id, b.ebay_id ";
註意這個復雜的查詢語句的條件
第一個條件
(a.ebay_paidtime between UNIX_TIMESTAMP(‘".$astart."‘) and UNIX_TIMESTAMP(‘".$aend."‘)
由於在ebay_paidtime字段有索引，如果只有這個條件，查詢速度很快，查詢一次不到一秒。但是因為後面還有兩個條件使用了 or, 這樣導致會導致了對ebay_order進行了全表查詢，而這個表有3百多萬條數據，所以查詢非常慢。
根據業務需求我們把三個用or 連接的查詢條件拆出來，分別進行查詢，最後用union語句連起來。這樣查詢的效率得到了大大的提高。修改後的查詢如下
$data1 ="select " . $fields_list . "
from ebay_order a left join ebay_orderdetail b on(a.ebay_ordersn=b.ebay_ordersn)
left join ebay_store c on (a.ebay_warehouse = c.id)
where a.ebay_combine !=1 and (a.resend_org_ebay_id=0 or a.resend_org_ebay_id is null) and
b.ebay_amount >0 and a.ebay_warehouse !=‘‘ and a.ebay_user=‘manwei‘
and a.ebay_paidtime between UNIX_TIMESTAMP(‘".$astart."‘) and UNIX_TIMESTAMP(‘".$aend."‘)";
$data2 = "select " . $fields_list . "
from ebay_order a left join ebay_orderdetail b on(a.ebay_ordersn=b.ebay_ordersn)
left join ebay_store c on (a.ebay_warehouse = c.id)
where a.ebay_combine !=1 and (a.resend_org_ebay_id=0 or a.resend_org_ebay_id is null) and
b.ebay_amount >0 and a.ebay_warehouse !=‘‘ and a.ebay_user=‘manwei‘
and (
a.shippedtime between UNIX_TIMESTAMP(‘".$astart_p."‘) and UNIX_TIMESTAMP(‘".$aend_p."‘) and
a.ebay_paidtime not between UNIX_TIMESTAMP(‘".$astart."‘) and UNIX_TIMESTAMP(‘".$aend."‘)
)";
if($last_ebay_id!=‘‘) {
$data3 = "select " . $fields_list . "
from ebay_order a left join ebay_orderdetail b on(a.ebay_ordersn=b.ebay_ordersn)
left join ebay_store c on (a.ebay_warehouse = c.id)
where a.ebay_combine !=1 and (a.resend_org_ebay_id=0 or a.resend_org_ebay_id is null) and
b.ebay_amount >0 and a.ebay_warehouse !=‘‘ and a.ebay_user=‘manwei‘
and a.ebay_id >=‘" .$last_ebay_id ."‘";
}
$data = "(" . $data1 . ")";
if($data2 != "") $data = $data . " union (". $data2 . ")";
if($data3 != "") $data = $data . " union (". $data3 . ")";小插曲，當我們分析data2的時候，無論如何給shippedtime加索引，只要查詢shippedtime都是全表查詢。仔細分析才知道原來在數據庫設計的時候，這個shippedtime的字段是varchar, 程序把時間戳保存成這種類型，自然沒有辦法使用適合我們需要的索引，解決的方法是通過alter語句先把shippedtime改成int 類型，再增加一個索引到這個字段。這樣這個查詢慢的問題就徹底得到解決了。
例子3：
$data = $isfesdb->query($data);
$quan = $isfesdb->num_rows($data);
for($i=0;$i<$quan;$i++){
{
...
$vv = "select goods_name, goods_weight from ebay_goods where goods_sn=‘".$sku[$i]."‘ limit 1";
$vv = $isfesdb->execute($vv);
$vv = $isfesdb->getResultArray($vv);
if(count($vv)==0){
...
$sku[$i] = str_replace(‘-FBA-FR‘,‘‘,$sku[$i]);
...
}
...
}從代碼上看，這個只是很簡單的查詢，ebay_goods也有索引，應該很快就能查詢到結果。但實際上整個流程跑下來很慢。仔細分析原因是因為$quan的數字太大，導致了for循環超過了10000次，這樣導致了$vv這個查詢進行了10000次。所以單獨查一條沒有性能問題，但是如果多次重復這樣的查詢就會引起性能問題。
解決的方法就是在for循環的前面先查詢ebay_goods全表，把這個表記錄到一個數組，然後在for循環裏使用素組的數據。因為ebay_goods這個數組只有幾千條記錄，這個方法是可行的。
修改程序變成：
$vv = $isfesdb->query("select goods_sn, goods_name, goods_weight from ebay_goods");
$vv_quan = $isfesdb->num_rows($vv);
$vv_result = $isfesdb->getResultArray($vv);
for($i=0; $i<$vv_quan; $i++) {
$goods_array[$vv_result[$i][‘goods_sn‘]] = array($vv_result[$i][‘goods_name‘], $vv_result[$i][‘goods_weight‘]);
}
for($i=0;$i<$quan;$i++)
{
...
if(!array_key_exists($sku[$i], $goods_array)){
...
$sku[$i] = str_replace(‘-FBA-FR‘,‘‘,$sku[$i]);
...
}
...
}我們采用數組的方法後，查詢也比舊方法效率提高好幾倍。這是因為現在我們的服務器配置的內存是足夠大的，PHP的運行也是足夠快的。瓶頸就在於php在等待mysql的查詢結果。所以我們先用一次查詢把數據庫結果組成了數組。
數據庫優化的三個例子