教程:使用Data Lake Analytics + OSS分析CSV格式的TPC-H数据集

简介: 0. Data Lake Analytics(DLA)简介 关于Data Lake的概念,更多阅读可以参考:https://en.wikipedia.org/wiki/Data_lake 以及AWS和Azure关于Data Lake的解读:https://amazonaws-china.

0. Data Lake Analytics(DLA)简介

关于Data Lake的概念,更多阅读可以参考:
https://en.wikipedia.org/wiki/Data_lake

以及AWS和Azure关于Data Lake的解读:
https://amazonaws-china.com/big-data/datalakes-and-analytics/what-is-a-data-lake/
https://azure.microsoft.com/en-us/solutions/data-lake/

终于,阿里云现在也有了自己的数据湖分析产品:https://www.aliyun.com/product/datalakeanalytics

可以点击申请使用(目前公测阶段还属于邀测模式,我们会尽快审批申请),体验本教程的TPC-H CSV数据格式的数据分析之旅。

产品文档:https://help.aliyun.com/product/70174.html

1. 开通Data Lake Analytics与OSS服务

如果您已经开通,可以跳过该步骤。如果没有开通,可以参考:https://help.aliyun.com/document_detail/70386.html
进行产品开通服务申请。

2. 下载TPC-H测试数据集

可以从这下载TPC-H 100MB的数据集:
https://public-datasets-cn-hangzhou.oss-cn-hangzhou.aliyuncs.com/tpch_100m_data.zip

3. 上传数据文件到OSS

登录阿里云官网的OSS控制台:https://oss.console.aliyun.com/overview
规划您要使用的OSS bucket,创建或选择好后,点击“文件管理”,因为有8个数据文件,为每个数据文件创建对应的文件目录:

image.png | left

创建好8个目录如下:

image.png | left

点击进入目录,上传相应的数据文件,例如,customer目录,则上传customer.tbl文件。

image.png | left

上传好后,如下图。然后,依次把其他7个数据文件也上传到对应的目录下。

image.png | left

至此,8个数据文件都上传到了您的OSS bucket中:

oss://xxx/tpch_100m/customer/customer.tbl
oss://xxx/tpch_100m/lineitem/lineitem.tbl
oss://xxx/tpch_100m/nation/nation.tbl
oss://xxx/tpch_100m/orders/orders.tbl
oss://xxx/tpch_100m/part/part.tbl
oss://xxx/tpch_100m/partsupp/partsupp.tbl
oss://xxx/tpch_100m/region/region.tbl
oss://xxx/tpch_100m/supplier/supplier.tbl

4. 登录Data Lake Analytics控制台

https://openanalytics.console.aliyun.com/
点击“登录数据库”,输入开通服务时分配的用户名和密码,登录Data Lake Analytics控制台。

5. 创建Schema和Table

输入创建SCHEMA的语句,点击“同步执行”。

CREATE SCHEMA tpch_100m with DBPROPERTIES(
  LOCATION = 'oss://test-bucket-julian-1/tpch_100m/',
  catalog='oss'
);

(注意:目前在同一个阿里云region,Data Lake Analytics的schema名全局唯一,建议schema名尽量根据业务定义,已有重名schema,在创建时会提示报错,则请换一个schema名字。)

Schema创建好后,在“数据库”的下拉框中,选择刚刚创建的schema。然后在SQL文本框中输入建表语句,点击同步执行。
建表语句语法参考:https://help.aliyun.com/document_detail/72006.html

image.png | left

TPC-H对应的8个表的建表语句如下,分别贴入文档框中执行(LOCATION子句中的数据文件位置请根据您的实际OSS bucket目录相应修改)。(注意:目前控制台中还不支持多个SQL语句执行,请单条语句执行。)

CREATE EXTERNAL TABLE nation (
    N_NATIONKEY INT, 
    N_NAME STRING,
       N_ID STRING,
    N_REGIONKEY INT, 
    N_COMMENT STRING
) 
ROW FORMAT DELIMITED FIELDS TERMINATED BY '|' 
STORED AS TEXTFILE 
LOCATION 'oss://test-bucket-julian-1/tpch_100m/nation';


CREATE EXTERNAL TABLE lineitem (
    L_ORDERKEY INT, 
    L_PARTKEY INT, 
    L_SUPPKEY INT, 
    L_LINENUMBER INT, 
    L_QUANTITY DOUBLE, 
    L_EXTENDEDPRICE DOUBLE, 
    L_DISCOUNT DOUBLE, 
    L_TAX DOUBLE, 
    L_RETURNFLAG STRING, 
    L_LINESTATUS STRING, 
    L_SHIPDATE DATE, 
    L_COMMITDATE DATE, 
    L_RECEIPTDATE DATE, 
    L_SHIPINSTRUCT STRING, 
    L_SHIPMODE STRING, 
    L_COMMENT STRING
) 
ROW FORMAT DELIMITED FIELDS TERMINATED BY '|' 
STORED AS TEXTFILE 
LOCATION 'oss://test-bucket-julian-1/tpch_100m/lineitem';


CREATE EXTERNAL TABLE orders (
    O_ORDERKEY INT, 
    O_CUSTKEY INT, 
    O_ORDERSTATUS STRING, 
    O_TOTALPRICE DOUBLE, 
    O_ORDERDATE DATE, 
    O_ORDERPRIORITY STRING, 
    O_CLERK STRING, 
    O_SHIPPRIORITY INT, 
    O_COMMENT STRING
) 
ROW FORMAT DELIMITED FIELDS TERMINATED BY '|' 
STORED AS TEXTFILE 
LOCATION 'oss://test-bucket-julian-1/tpch_100m/orders';


CREATE EXTERNAL TABLE supplier (
    S_SUPPKEY INT, 
    S_NAME STRING, 
    S_ADDRESS STRING, 
    S_NATIONKEY INT, 
    S_PHONE STRING, 
    S_ACCTBAL DOUBLE, 
    S_COMMENT STRING
) 
ROW FORMAT DELIMITED FIELDS TERMINATED BY '|' 
STORED AS TEXTFILE 
LOCATION 'oss://test-bucket-julian-1/tpch_100m/supplier';


CREATE EXTERNAL TABLE partsupp (
    PS_PARTKEY INT, 
    PS_SUPPKEY INT, 
    PS_AVAILQTY INT, 
    PS_SUPPLYCOST DOUBLE, 
    PS_COMMENT STRING
) 
ROW FORMAT DELIMITED FIELDS TERMINATED BY '|' 
STORED AS TEXTFILE 
LOCATION 'oss://test-bucket-julian-1/tpch_100m/partsupp';


CREATE EXTERNAL TABLE customer (
    C_CUSTKEY INT, 
    C_NAME STRING, 
    C_ADDRESS STRING, 
    C_NATIONKEY INT, 
    C_PHONE STRING, 
    C_ACCTBAL DOUBLE, 
    C_MKTSEGMENT STRING, 
    C_COMMENT STRING
) 
ROW FORMAT DELIMITED FIELDS TERMINATED BY '|' 
STORED AS TEXTFILE 
LOCATION 'oss://test-bucket-julian-1/tpch_100m/customer';


CREATE EXTERNAL TABLE part (
    P_PARTKEY INT, 
    P_NAME STRING, 
    P_MFGR STRING, 
    P_BRAND STRING, 
    P_TYPE STRING, 
    P_SIZE INT, 
    P_CONTAINER STRING, 
    P_RETAILPRICE DOUBLE, 
    P_COMMENT STRING
) 
ROW FORMAT DELIMITED FIELDS TERMINATED BY '|' 
STORED AS TEXTFILE 
LOCATION 'oss://test-bucket-julian-1/tpch_100m/part';


CREATE EXTERNAL TABLE region (
    R_REGIONKEY INT, 
    R_NAME STRING, 
    R_COMMENT STRING
) 
ROW FORMAT DELIMITED FIELDS TERMINATED BY '|' 
STORED AS TEXTFILE 
LOCATION 'oss://test-bucket-julian-1/tpch_100m/region';

建表完毕后,刷新页面,在左边导航条中能看到schema下的8张表。

image.png | left

6. 执行TPC-H查询

TPC-H总共22条查询,如下:
Q1:

SELECT   l_returnflag,
         l_linestatus,
         Sum(l_quantity)                                       AS sum_qty,
         Sum(l_extendedprice)                                  AS sum_base_price,
         Sum(l_extendedprice * (1 - l_discount))               AS sum_disc_price,
         Sum(l_extendedprice * (1 - l_discount) * (1 + l_tax)) AS sum_charge,
         Avg(l_quantity)                                       AS avg_qty,
         Avg(l_extendedprice)                                  AS avg_price,
         Avg(l_discount)                                       AS avg_disc,
         Count(*)                                              AS count_order
FROM     lineitem
WHERE    l_shipdate <= date '1998-12-01' - INTERVAL '93' day
GROUP BY l_returnflag,
         l_linestatus
ORDER BY l_returnflag,
         l_linestatus
LIMIT    1;

Q2:

SELECT   s_acctbal,
         s_name,
         n_name,
         p_partkey,
         p_mfgr,
         s_address,
         s_phone,
         s_comment
FROM     part,
         supplier,
         partsupp,
         nation,
         region
WHERE    p_partkey = ps_partkey
AND      s_suppkey = ps_suppkey
AND      p_size = 35
AND      p_type LIKE '%NICKEL'
AND      s_nationkey = n_nationkey
AND      n_regionkey = r_regionkey
AND      r_name = 'MIDDLE EAST'

Q3:

SELECT   l_orderkey,
         Sum(l_extendedprice * (1 - l_discount)) AS revenue,
         o_orderdate,
         o_shippriority
FROM     customer,
         orders,
         lineitem
WHERE    c_mktsegment = 'AUTOMOBILE'
AND      c_custkey = o_custkey
AND      l_orderkey = o_orderkey
AND      o_orderdate < date '1995-03-31'
AND      l_shipdate >  date '1995-03-31'
GROUP BY l_orderkey,
         o_orderdate,
         o_shippriority
ORDER BY revenue DESC,
         o_orderdate
LIMIT    10;

Q4:

SELECT   o_orderpriority,
         Count(*) AS order_count
FROM     orders,
         lineitem
WHERE    o_orderdate >= date '1997-10-01'
AND      o_orderdate <  date '1997-10-01' + INTERVAL '3' month
AND      l_orderkey = o_orderkey
AND      l_commitdate < l_receiptdate
GROUP BY o_orderpriority
ORDER BY o_orderpriority
LIMIT    1;

Q5:

SELECT   n_name,
         Sum(l_extendedprice * (1 - l_discount)) AS revenue
FROM     customer,
         orders,
         lineitem,
         supplier,
         nation,
         region
WHERE    c_custkey = o_custkey
AND      l_orderkey = o_orderkey
AND      l_suppkey = s_suppkey
AND      c_nationkey = s_nationkey
AND      s_nationkey = n_nationkey
AND      n_regionkey = r_regionkey
AND      r_name = 'ASIA'
AND      o_orderdate >= date '1995-01-01'
AND      o_orderdate <  date '1995-01-01' + INTERVAL '1' year
GROUP BY n_name
ORDER BY revenue DESC
LIMIT    1;

Q6:

SELECT sum(l_extendedprice * l_discount) AS revenue
FROM lineitem
WHERE l_shipdate >= date '1995-01-01'
AND l_shipdate < date '1995-01-01' + interval '1' year
AND l_discount between 0.04 - 0.01 AND 0.04 + 0.01
AND l_quantity < 24
LIMIT 1;

Q7:

SELECT   supp_nation,
         cust_nation,
         l_year,
         Sum(volume) AS revenue
FROM     (
                SELECT n1.n_name                          AS supp_nation,
                       n2.n_name                          AS cust_nation,
                       Extract(year FROM l_shipdate)      AS l_year,
                       l_extendedprice * (1 - l_discount) AS volume
                FROM   supplier,
                       lineitem,
                       orders,
                       customer,
                       nation n1,
                       nation n2
                WHERE  s_suppkey = l_suppkey
                AND    o_orderkey = l_orderkey
                AND    c_custkey = o_custkey
                AND    s_nationkey = n1.n_nationkey
                AND    c_nationkey = n2.n_nationkey
                AND    ( (
                                     n1.n_name = 'GERMANY'
                              AND    n2.n_name = 'INDIA')
                       OR     (
                                     n1.n_name = 'INDIA'
                              AND    n2.n_name = 'GERMANY') )
                AND    l_shipdate BETWEEN date '1995-01-01' AND    date '1996-12-31' ) AS shipping
GROUP BY supp_nation,
         cust_nation,
         l_year
ORDER BY supp_nation,
         cust_nation,
         l_year
LIMIT    1;

Q8:

SELECT   o_year,
         Sum(
         CASE
                  WHEN nation = 'INDIA' THEN volume
                  ELSE 0
         end) / Sum(volume) AS mkt_share
FROM     (
                SELECT Extract(year FROM o_orderdate)     AS o_year,
                       l_extendedprice * (1 - l_discount) AS volume,
                       n2.n_name                          AS nation
                FROM   part,
                       supplier,
                       lineitem,
                       orders,
                       customer,
                       nation n1,
                       nation n2,
                       region
                WHERE  p_partkey = l_partkey
                AND    s_suppkey = l_suppkey
                AND    l_orderkey = o_orderkey
                AND    o_custkey = c_custkey
                AND    c_nationkey = n1.n_nationkey
                AND    n1.n_regionkey = r_regionkey
                AND    r_name = 'ASIA'
                AND    s_nationkey = n2.n_nationkey
                AND    o_orderdate BETWEEN date '1995-01-01' AND    date '1996-12-31'
                AND    p_type = 'STANDARD ANODIZED STEEL' ) AS all_nations
GROUP BY o_year
ORDER BY o_year
LIMIT    1;

Q9:

SELECT   nation,
         o_year,
         Sum(amount) AS sum_profit
FROM     (
                SELECT n_name                                                          AS nation,
                       Extract(year FROM o_orderdate) AS o_year,
                       l_extendedprice * (1 - l_discount) - ps_supplycost * l_quantity AS amount
                FROM   part,
                       supplier,
                       lineitem,
                       partsupp,
                       orders,
                       nation
                WHERE  s_suppkey = l_suppkey
                AND    ps_suppkey = l_suppkey
                AND    ps_partkey = l_partkey
                AND    p_partkey = l_partkey
                AND    o_orderkey = l_orderkey
                AND    s_nationkey = n_nationkey
                AND    p_name LIKE '%aquamarine%' ) AS profit
GROUP BY nation,
         o_year
ORDER BY nation,
         o_year DESC
LIMIT    1;

Q10:

SELECT   c_custkey,
         c_name,
         Sum(l_extendedprice * (1 - l_discount)) AS revenue,
         c_acctbal,
         n_name,
         c_address,
         c_phone,
         c_comment
FROM     customer,
         orders,
         lineitem,
         nation
WHERE    c_custkey = o_custkey
AND      l_orderkey = o_orderkey
AND      o_orderdate >= date '1994-08-01'
AND      o_orderdate <  date '1994-08-01' + INTERVAL '3' month
AND      l_returnflag = 'R'
AND      c_nationkey = n_nationkey
GROUP BY c_custkey,
         c_name,
         c_acctbal,
         c_phone,
         n_name,
         c_address,
         c_comment
ORDER BY revenue DESC
LIMIT    20;

Q11:

SELECT   ps_partkey,
         Sum(ps_supplycost * ps_availqty) AS value
FROM     partsupp,
         supplier,
         nation
WHERE    ps_suppkey = s_suppkey
AND      s_nationkey = n_nationkey
AND      n_name = 'PERU'
GROUP BY ps_partkey
HAVING   Sum(ps_supplycost * ps_availqty) >
(
SELECT Sum(ps_supplycost * ps_availqty) * 0.0001000000 as sum_value
  FROM partsupp,
       supplier,
       nation
  WHERE  ps_suppkey = s_suppkey
  AND    s_nationkey = n_nationkey
  AND    n_name = 'PERU'
)
ORDER BY value DESC
LIMIT    1;

Q12:

SELECT l_shipmode, sum(case when o_orderpriority = '1-URGENT' or o_orderpriority = '2-HIGH' then 1
    else 0
end) AS high_line_count, sum(case when o_orderpriority <> '1-URGENT' and o_orderpriority <> '2-HIGH' then 1
else 0
end) AS low_line_count
FROM orders,
     lineitem
WHERE o_orderkey = l_orderkey
AND l_shipmode in ('MAIL', 'TRUCK')
AND l_commitdate < l_receiptdate
AND l_shipdate < l_commitdate
AND l_receiptdate >= date '1996-01-01'
AND l_receiptdate < date '1996-01-01' + interval '1' year
GROUP BY l_shipmode
ORDER BY l_shipmode
LIMIT 1;

Q13:

SELECT c_count, count(*) AS custdist
FROM (
    SELECT c_custkey, count(o_orderkey) AS c_count
    FROM customer,
         orders
    WHERE c_custkey = o_custkey
    AND o_comment NOT LIKE '%pending%accounts%'
    GROUP BY c_custkey ) AS c_orders
GROUP BY c_count
ORDER BY custdist DESC, c_count DESC
LIMIT 1;

Q14:

SELECT 100.00 * sum(case when p_type like 'PROMO%' then l_extendedprice * (1 - l_discount)
    else 0
end) / sum(l_extendedprice * (1 - l_discount)) AS promo_revenue
FROM lineitem,
     part
WHERE l_partkey = p_partkey
AND l_shipdate >= date '1996-01-01'
AND l_shipdate < date '1996-01-01' + interval '1' month
LIMIT 1;

Q15:

WITH revenue0 AS
(
SELECT l_suppkey AS supplier_no, sum(l_extendedprice * (1 - l_discount)) AS total_revenue
FROM lineitem
WHERE l_shipdate >= date '1993-01-01'
AND l_shipdate < date '1993-01-01' + interval '3' month
GROUP BY l_suppkey
)
SELECT s_suppkey, s_name, s_address, s_phone, total_revenue
FROM supplier, revenue0
WHERE s_suppkey = supplier_no
AND total_revenue IN (
    SELECT max(total_revenue)
    FROM revenue0 )
ORDER BY s_suppkey;

Q16:

SELECT p_brand, p_type, p_size, count(distinct ps_suppkey) AS supplier_cnt
FROM partsupp,
     part
WHERE p_partkey = ps_partkey
AND p_brand <> 'Brand#23'
AND p_type NOT LIKE 'PROMO BURNISHED%'
AND p_size IN (1, 13, 10, 28, 21, 35, 31, 11)
AND ps_suppkey NOT IN (
    SELECT s_suppkey
    FROM supplier
    WHERE s_comment LIKE '%Customer%Complaints%' )
GROUP BY p_brand, p_type, p_size
ORDER BY supplier_cnt DESC, p_brand, p_type, p_size
LIMIT 1;

Q17:

SELECT
    sum(l_extendedprice) / 7.0 AS avg_yearly
FROM
    lineitem,
    part
WHERE p_partkey = l_partkey
    AND p_brand = 'Brand#44'
    AND p_container = 'WRAP PKG'
    AND l_quantity < (
        SELECT
            0.2 * avg(l_quantity)
        FROM
            lineitem, part
        WHERE
            l_partkey = p_partkey
    );

Q18:

SELECT c_name, c_custkey, o_orderkey, o_orderdate, o_totalprice, sum(l_quantity)
FROM customer,
     orders,
     lineitem
WHERE o_orderkey IN (
      SELECT l_orderkey
      FROM lineitem
      GROUP BY l_orderkey
      HAVING sum(l_quantity) > 315 )
AND c_custkey = o_custkey
AND o_orderkey = l_orderkey
GROUP BY c_name, c_custkey, o_orderkey, o_orderdate, o_totalprice
ORDER BY o_totalprice DESC, o_orderdate
LIMIT 100;

Q19:

SELECT sum(l_extendedprice* (1 - l_discount)) AS revenue
FROM lineitem,
     part
WHERE ( p_partkey = l_partkey and p_brand = 'Brand#12'
        and p_container in ('SM CASE', 'SM BOX', 'SM PACK', 'SM PKG')
        and l_quantity >= 6 and l_quantity <= 6 + 10
        and p_size between 1 and 5
        and l_shipmode in ('AIR', 'AIR REG')
        and l_shipinstruct = 'DELIVER IN PERSON' )
    or ( p_partkey = l_partkey and p_brand = 'Brand#13'
        and p_container in ('MED BAG', 'MED BOX', 'MED PKG', 'MED PACK')
        and l_quantity >= 10 and l_quantity <= 10 + 10
        and p_size between 1 and 10
        and l_shipmode in ('AIR', 'AIR REG')
        and l_shipinstruct = 'DELIVER IN PERSON' )
    or ( p_partkey = l_partkey and p_brand = 'Brand#24'
        and p_container in ('LG CASE', 'LG BOX', 'LG PACK', 'LG PKG')
        and l_quantity >= 21 and l_quantity <= 21 + 10
        and p_size between 1 and 15
        and l_shipmode in ('AIR', 'AIR REG')
        and l_shipinstruct = 'DELIVER IN PERSON' )
LIMIT 1;

Q20:

with temp_table as
(
 select 0.5 * sum(l_quantity) as col1
 from lineitem,
      partsupp
 where l_partkey = ps_partkey and l_suppkey = ps_suppkey
 and l_shipdate >= date '1993-01-01'
 and l_shipdate < date '1993-01-01' + interval '1' year
)
select s_name, s_address
from supplier,
     nation
where s_suppkey in (
    select ps_suppkey
    from partsupp,
         temp_table
    where ps_partkey in (
        select p_partkey
        from part
        where p_name like 'dark%' )
        and ps_availqty > temp_table.col1 )
    and s_nationkey = n_nationkey and n_name = 'JORDAN'
order by s_name
limit 1;

Q21:

select
    s_name,
    count(*) as numwait
from
    supplier,
    lineitem l1,
    orders,
    nation
where
    s_suppkey = l1.l_suppkey
    and o_orderkey = l1.l_orderkey
    and o_orderstatus = 'F'
    and l1.l_receiptdate > l1.l_commitdate
    and exists (
        select
            *
        from
            lineitem l2
        where
            l2.l_orderkey = l1.l_orderkey
            and l2.l_suppkey <> l1.l_suppkey
    )
    and not exists (
        select
            *
        from
            lineitem l3
        where
            l3.l_orderkey = l1.l_orderkey
            and l3.l_suppkey <> l1.l_suppkey
            and l3.l_receiptdate > l3.l_commitdate
    )
    and s_nationkey = n_nationkey
    and n_name = 'SAUDI ARABIA'
group by
    s_name
order by
    numwait desc,
    s_name
limit 100;

Q22:

with temp_table_1 as
(
  select avg(c_acctbal) as avg_value
  from customer
  where c_acctbal > 0.00 and substring(c_phone from 1 for 2)
  in ('33', '29', '37', '35', '25', '27', '43')
),
temp_table_2 as
(
  select count(*) as count1
  from orders, customer
  where o_custkey = c_custkey
)
select cntrycode, count(*) as numcust, sum(c_acctbal) as totacctbal
from (
    select substring(c_phone from 1 for 2) as cntrycode, c_acctbal
    from customer, temp_table_1, temp_table_2
    where substring(c_phone
        from 1
        for 2) in ('33', '29', '37', '35', '25', '27', '43')
        and c_acctbal > temp_table_1.avg_value
        and temp_table_2.count1 = 0) as custsale
group by cntrycode
order by cntrycode
limit 1;

7. 异步执行查询

Data Lake Analytics支持“同步执行”模式和“异步执行”模式。“同步执行”模式下,控制台界面等待执行结果返回;“异步执行”模式下,立刻返回查询任务的ID。

image.png | left

点击“执行状态”,可以看到该异步查询任务的执行状态,主要分为:“RUNNING”,“SUCCESS”,“FAILURE”。

image.png | left

点击“刷新”,当STATUS变为“SUCCESS”时,表示查询成功,同时可查看查询耗时“ELAPSE_TIME”和查询扫描的数据字节数“SCANNED_DATA_BYTES”。

image.png | left

8. 查看查询历史

点击“执行历史”,可以看到您执行的查询的历史详细信息,包括:
1)查询语句;
2)查询耗时与执行具体时间;
3)查询结果返回行数;
4)查询状态;
5)查询扫描的字节数;
6)结果集回写到的目标OSS文件(Data Lake Analytics会将查询结果集保存用户的bucket中)。

image.png | left

查询结果文件自动上传到用户同region的OSS bucket中,其中包括结果数据文件和结果集元数据描述文件。

{QueryLocation}/{query_name}|Unsaved}/{yyyy}/{mm}/{dd}/{query_id}/xxx.csv
{QueryLocation}/{query_name}|Unsaved}/{yyyy}/{mm}/{dd}/{query_id}/xxx.csv.metadata

其中QueryLocation为:

aliyun-oa-query-results-<your_account_id>-<oss_region>

image.png | left

9. 后续

至此,本教程一步一步教您如何利用Data Lake Analytics云产品分析您OSS上的CSV格式的数据文件。除了CSV文件外,Data Lake Analytics还支持Parquet、ORC、json、RCFile、AVRO等多种格式文件的数据分析能力。特别是Parquet、ORC,相比CSV文件,有极大的性能和成本优势(同样内容的数据集,拥有更小的存储空间、更快的查询性能,这也意味着更低的分析成本)。
后续陆续会有更多教程和文章,手把手教您轻松使用Data Lake Analytics进行数据湖上数据分析和探索,开启您的云上低成本、即存即用的数据分析和探索之旅。
G

相关实践学习
借助OSS搭建在线教育视频课程分享网站
本教程介绍如何基于云服务器ECS和对象存储OSS,搭建一个在线教育视频课程分享网站。
目录
相关文章
|
6月前
|
存储 监控 API
oss教程
oss教程
261 1
|
1月前
|
存储 Java 开发工具
【三方服务集成】最新版 | 阿里云OSS对象存储服务使用教程(包含OSS工具类优化、自定义阿里云OSS服务starter)
阿里云OSS(Object Storage Service)是一种安全、可靠且成本低廉的云存储服务,支持海量数据存储。用户可通过网络轻松存储和访问各类文件,如文本、图片、音频和视频等。使用OSS后,项目中的文件上传业务无需在服务器本地磁盘存储文件,而是直接上传至OSS,由其管理和保障数据安全。此外,介绍了OSS服务的开通流程、Bucket创建、AccessKey配置及环境变量设置,并提供了Java SDK示例代码,帮助用户快速上手。最后,展示了如何通过自定义starter简化工具类集成,实现便捷的文件上传功能。
【三方服务集成】最新版 | 阿里云OSS对象存储服务使用教程(包含OSS工具类优化、自定义阿里云OSS服务starter)
|
4月前
|
SQL 分布式计算 大数据
MaxCompute操作报错合集之在读取OSS遇到格式报错,该怎么办
MaxCompute是阿里云提供的大规模离线数据处理服务,用于大数据分析、挖掘和报表生成等场景。在使用MaxCompute进行数据处理时,可能会遇到各种操作报错。以下是一些常见的MaxCompute操作报错及其可能的原因与解决措施的合集。
|
5月前
|
SQL 分布式计算 DataWorks
DataWorks产品使用合集之如何将CSV文件从阿里云OSS同步到ODPS表,并且使用列作为表分区
DataWorks作为一站式的数据开发与治理平台,提供了从数据采集、清洗、开发、调度、服务化、质量监控到安全管理的全套解决方案,帮助企业构建高效、规范、安全的大数据处理体系。以下是对DataWorks产品使用合集的概述,涵盖数据处理的各个环节。
DataWorks产品使用合集之如何将CSV文件从阿里云OSS同步到ODPS表,并且使用列作为表分区
|
6月前
|
SQL 分布式计算 监控
基于阿里云 EMR Serverless Spark 版快速搭建OSS日志分析应用
本文演示了使用 EMR Serverless Spark 产品搭建一个日志分析应用的全流程,包括数据开发和生产调度以及交互式查询等场景。
56592 7
基于阿里云 EMR Serverless Spark 版快速搭建OSS日志分析应用
|
5月前
|
存储 分布式计算 大数据
MaxCompute产品使用问题之创建了oss外表,格式指定的parquet,然后执行的写入,发现不是标准parquet的格式,该怎么办
MaxCompute作为一款全面的大数据处理平台,广泛应用于各类大数据分析、数据挖掘、BI及机器学习场景。掌握其核心功能、熟练操作流程、遵循最佳实践,可以帮助用户高效、安全地管理和利用海量数据。以下是一个关于MaxCompute产品使用的合集,涵盖了其核心功能、应用场景、操作流程以及最佳实践等内容。
|
4月前
|
分布式计算 DataWorks 数据管理
DataWorks操作报错合集之使用OSS读取CSV文件到ODPS时遇到报错,一般是什么导致的
DataWorks是阿里云提供的一站式大数据开发与治理平台,支持数据集成、数据开发、数据服务、数据质量管理、数据安全管理等全流程数据处理。在使用DataWorks过程中,可能会遇到各种操作报错。以下是一些常见的报错情况及其可能的原因和解决方法。
|
5月前
|
存储 DataWorks 关系型数据库
DataWorks产品使用合集之在使用数据集成中的同步任务从mysql同步表到oss,存储为csv时,最终生成的文件中没有表头,这个属性可以在哪里配置么
DataWorks作为一站式的数据开发与治理平台,提供了从数据采集、清洗、开发、调度、服务化、质量监控到安全管理的全套解决方案,帮助企业构建高效、规范、安全的大数据处理体系。以下是对DataWorks产品使用合集的概述,涵盖数据处理的各个环节。
|
5月前
|
存储 分布式计算 关系型数据库
实时数仓 Hologres产品使用合集之是否提供相应的功能接口和指令,可以将数据从OSS存储同步到Hologres中进行分析
实时数仓Hologres的基本概念和特点:1.一站式实时数仓引擎:Hologres集成了数据仓库、在线分析处理(OLAP)和在线服务(Serving)能力于一体,适合实时数据分析和决策支持场景。2.兼容PostgreSQL协议:Hologres支持标准SQL(兼容PostgreSQL协议和语法),使得迁移和集成变得简单。3.海量数据处理能力:能够处理PB级数据的多维分析和即席查询,支持高并发低延迟查询。4.实时性:支持数据的实时写入、实时更新和实时分析,满足对数据新鲜度要求高的业务场景。5.与大数据生态集成:与MaxCompute、Flink、DataWorks等阿里云产品深度融合,提供离在线
|
6月前
|
分布式计算 Java 大数据
MaxCompute产品使用合集之大数据计算MaxCompute外部表映射了oss中的csv文件,看到"\N"被解析为"N",是什么原因
MaxCompute作为一款全面的大数据处理平台,广泛应用于各类大数据分析、数据挖掘、BI及机器学习场景。掌握其核心功能、熟练操作流程、遵循最佳实践,可以帮助用户高效、安全地管理和利用海量数据。以下是一个关于MaxCompute产品使用的合集,涵盖了其核心功能、应用场景、操作流程以及最佳实践等内容。
下一篇
无影云桌面