piwik 高级搜索要点

piwik搜索要点在于getLastVisitsDetails函数,如下:

function getLastVisitsDetails( $idSite, $period = false, $date = false, $segment = false, $filter_limit = false, $maxIdVisit = false, $minTimestamp = false )

根据参数的不同可以设置相关的搜索,其中$idSite位站点编号,$period为时期(包括年,月),$date为日期,$segment为一系列筛选条件,$filter_limit为返回的条数。其中最重要的参数为$segment,可以定义一系列条件:

可以定义的参数如下:

browserName Browser
Example values: FF, IE, CH, SF, OP, etc.
browserVersion Browser version
Example values: 1.0, 8.0, etc.
continent Continent
Example values: eur, asi, amc, amn, ams, afr, ant, oce
country Country
Example values: de, us, fr, in, es, etc.
visitLocalHour Local time
Example values: 0, 1, 2, 3, ..., 20, 21, 22, 23
operatingSystem Operating system
Example values: WXP, WI7, MAC, LIN, AND, IPD, etc.
provider Provider
Example values: comcast.net, proxad.net, etc.
resolution Resolution
Example values: 1280x1024, 800x600, etc.
visitServerHour Server time
Example values: 0, 1, 2, 3, ..., 20, 21, 22, 23
visitEcommerceStatus Visit Ecommerce status at the end of the visit. For example, to select all visits that have made an Ecommerce order, the API request would contain “&segment=visitEcommerceStatus==ordered,visitEcommerceStatus==orderedThenAbandonedCart”
Example values: none, ordered, abandonedCart, orderedThenAbandonedCart
visitConvertedGoalId Visit converted a specific Goal Id
Example values: 1, 2, 3, etc.
visitConverted Visit converted at least one Goal
Example values: 0, 1
visitorId Visitor ID
Example values: 34c31e04394bdc63 - any 16 Hexadecimal chars ID, which can be fetched using the Tracking API function getVisitorId()
visitIp Visitor IP
Note: This segment can only be used by an Admin user
Example values: 13.54.122.1, etc.
visitorType Visitor type. For example, to select all visitors who have returned to the website, including those who have bought something in their previous visits, the API request would contain “&segment=visitorType==returning,visitorType==returningCustomer”
Example values: new, returning, returningCustomer
Referrers
referrerKeyword Keyword
Example values: Encoded%20Keyword, keyword
referrerName Referrer Name
Example values: twitter.com, www.facebook.com, Bing, Google, Yahoo, CampaignName
referrerType Referrer Type
Example values: direct, search, website, campaign
referrerUrl Referrer URL
Example values: http%3A%2F%2Fwww.example.org%2Freferer-page.htm

用线性回归方法计算直线斜率

关于线性回归可以参考百度知道。其中采用最小二乘法可以比较容易的算出过往设备负载增长的斜率,具体公式如下:

下面代码简单枚举历史10个点来计算该设备负载增长率:

PHP语言:
//Y坐标值表示设备历史负载
$y = array(52.09, 52.4, 53.29, 54.22, 55.15, 55.83, 56.89, 56.98, 57.55, 57.8);

//X坐标值表示顺序天数
$x = array(1, 2, 3, 4, 5, 6, 7, 8, 9, 10);

//计算X和Y均值
$ax = array_sum($x)/count($x);
$ay = array_sum($y)/count($y);

//计算斜率公式中的分母(em)和分子(ez)
$em = 0;
$ez = 0;
for ($i = 0; $i < count($x); $i++) {
//分母求和
$em += (($x[$i] - $ax) * ($y[$i] - $ay));
//分子求和
$ez += pow(($x[$i] - $ax), 2);
}

//斜率0.69
echo $em/$ez;

//第十一个点预测负载值58.34
echo $em/$ez * 10 + $ay - ($em/$ez)*$ax;

很多概念都不甚懂,反正数学是没有学好的,找来公式代一代,嘿嘿,还算可以,对于波动比较大的就比较难以预测,这个近似值还是很有参考意义的。

回归直线:

如果散点图中点的分布从整体看大致在一条直线附近,我们就称这两个变量之间具有线性相关关系,这条直线叫做回归直线。根据不同的标准,可以画出不同的直线来近似表示这种线性相关关系。比如可以连接最左侧点和最右侧点得到一条直线,或者让画出的直线上方的点和下方的点数目相等。当所有数据点都分布在一条直线附近,显然这样的直线还可以画出许多条,而我们希望找出其中的一条,它能最好地反映x与Y的关系,换言之,我们要找出一条直线,使这条直线“最贴近”已知的数据点。记此直线方程为y^=a+bx。这里在y的上方加记号“^”是为了区分Y的实际值y,表示x取值xi(i=1,2,3……,n)时,Y相应的观察值为yi,而直线上对应于xi的纵坐标是yi^=a+bxi(i为x右下角的数值)。y^=a+bx式叫做Y对x的回归直线方程,b叫回归系数。要确定回归直线方程,只要确定a于回归系数b。

各linux版本重启apache命令

Slackware Linux命令:/etc/rc.d/rc.httpd restart

ubuntu、Debian 系统命令:

/etc/init.d/apache2 restart

Fedora 、Redhat、CentOS系统重启Apache命令:

/etc/init.d/httpd restart

service httpd restart(CentOS 成功)