Spark Scala程式設計常用技巧集錦

(1) 獲取filesystem

//1. 生成filesystem

def gethdfs
(path: string)
: filesystem =

def findcandidate

(filesystem: filesystem, fspath: string)
: path =

spark.read.text(finalpath)：將檔案讀取為dataframe

//獲取最新目錄

val validpath =
findcandidate
(gethdfs
(path)
, path)
println
("validfilepath: "
+ validpath)
val finalpath = validpath.tostring.
concat
("/part-*"
)println
("finalpath: "
+ finalpath)
val result = spark.read.
text
(finalpath)

val list = result.

collect()
for(row <
- list)
val features = json.
getjsonarray
("feature"
).toarray
val imgid = json.
getstring
("img_id"
)      val imgurl = json.
getstring
("img_url"
)      val width = json.
getintvalue
("width"
)      val height = json.
getintvalue
("height"
)      val date = json.
getstring
("date"
)      val isimg = json.
getstring
("type"
)      val extention = json.
getstring
("extention"
)      val path = json.
getstring
("path"
)      val source = json.
getstring
("source"
)      datalist.
add(
row(adidslist.toarray, features, imgid, imgurl, width, height, date, isimg, extention, path, source)
)}

其中，datalist需要事先定義好row的scheme，如下所示

val schema =

structtype
(list
(structfield
("s_ad_id"
,arraytype
(longtype,
true),
true),
structfield
("feature"
,arraytype
(stringtype,
true),
true),
structfield
("img_id"
, stringtype,
true),
structfield
("img_url"
, stringtype,
true),
structfield
("width"
, integertype,
true),
structfield
("height"
, integertype,
true),
structfield
("date"
, stringtype,
true),
structfield
("format_type"
, stringtype,
true),
structfield
("extention"
, stringtype,
true),
structfield
("path"
, stringtype,
true),
structfield
("source"
, stringtype,
true))
)    val datalist =
newutil.arraylist
[row]
()

var df2 = spark.

createdataframe
(datalist, schema)

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