Using Data Lake Analytics + OSS to analyze TPC-H datasets in CSV format

Keywords: Blockchain SQL Database AWS JSON

Introduction to Data Lake Analytics (DLA)

For more reading about the concept of Data Lake, you can refer to:
https://en.wikipedia.org/wiki/Data_lake

And AWS and Azure's interpretation of Data Lake:
https://amazonaws-china.com/big-data/datalakes-and-analytics/what-is-a-data-lake/
https://azure.microsoft.com/en-us/solutions/data-lake/

Finally, Aliyun now has its own data Lake analysis products: https://www.aliyun.com/product/datalakeanalytics

You can click on the application (the current public testing stage is still an invitation mode, we will approve the application as soon as possible), and experience the data analysis journey of TPC-H CSV data format in this tutorial.

Product documentation: https://help.aliyun.com/product/70174.html

1. Opening Data Lake Analytics and OSS Services

If you have already started, you can skip this step. If not, you can refer to: https://help.aliyun.com/document_detail/70386.html
Apply for product opening service.

2. Download TPC-H Test Data Set

You can download the TPC-H 100MB dataset from here:
https://public-datasets-cn-hangzhou.oss-cn-hangzhou.aliyuncs.com/tpch_100m_data.zip

3. Upload data files to OSS

OSS console on Aliyun official website: https://oss.console.aliyun.com/overview
Plan the OSS bucket you want to use. After creating or selecting it, click on File Management, because there are eight data files, create a corresponding file directory for each data file:

Create 8 directories as follows:

Click to enter the directory and upload the corresponding data files, such as the customer directory, then upload the customer.tbl file.

After uploading, as shown below. Then, the other seven data files are uploaded to the corresponding directory in turn.

So far, eight data files have been uploaded to your OSS bucket:

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. Log on to the Data Lake Analytics console

https://openanalytics.console.aliyun.com/
Click "Log in to the database", enter the username and password assigned when opening the service, and log in to the Data Lake Analysis console.

5. Create Schema and Table

Enter the statement to create SCHEMA and click Synchronize Execution.

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

(Note: At present, the schema name of Data Lake Analytics is globally unique in the same Aliyun region. It is suggested that the schema name should be based on the business definition as far as possible. There is already a renamed schema. When creating the schema, an error will be prompted. Please change the schema name.)

When Schema is created, in the drop-down box of the Database, select the schema you just created. Then enter the table-building statement in the SQL text box and click Synchronize Execution.
Grammatical Reference for Table-building Statements: https://help.aliyun.com/document_detail/72006.html

The table-building statements of eight tables corresponding to TPC-H are as follows, which are pasted into the document box and executed separately. (The location of data files in the LOCATION clause should be modified according to your actual OSS bucket directory.) (Note: At present, there is no support for multiple SQL statements in the console. Please execute a single statement.)

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';

After the table is built, refresh the page and you can see eight tables under schema in the left navigation bar.

6. Perform TPC-H queries

TPC-H has 22 queries as follows:
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. Asynchronous execution of queries

Data Lake Analytics supports both synchronous and asynchronous execution modes. In "synchronous execution" mode, the console interface waits for the execution result to return; in "asynchronous execution" mode, the ID of the query task is returned immediately.

Click on "Execution Status" to see the execution status of the asynchronous query task, mainly divided into: "RUNNING", "SUCCESS", "FAILURE".

Click "Refresh" when STATUS changes to "SUCCESS" to indicate that the query is successful, while viewing the query time-consuming "ELAPSE_TIME" and the number of data bytes scanned by the query "SCANNED_DATA_BYTES".

8. View query history

Click "Execution History" to see the historical details of the queries you executed, including:
1) Query statements;
2) Query time-consuming and execution time;
3) The number of rows returned from the query results;
4) Query status;
5) The number of bytes scanned by query;
6) The result set is written back to the target OSS file (Data Lake Analytics saves the query result set in the user's bucket).

The query result file is automatically uploaded to the OSS bucket of the user and region, including the result data file and the metadata description file of the result set.

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

Query Location is:

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

9. follow up

So far, this tutorial teaches you step by step how to use Data Lake Analytics cloud products to analyze CSV-formatted data files on your OSS. In addition to CSV files, Data Lake Analytics also supports data analysis capabilities of Parquet, ORC, json, RCFile, AVRO and other format files. Parquet and ORC, in particular, have great performance and cost advantages over CSV files (data sets with the same content have smaller storage space and faster query performance, which also means lower analysis costs).
There will be more tutorials and articles to teach you how to easily use Data Lake Analytics for data analysis and Exploration on the data lake, opening up your low-cost, off-the-shelf data analysis and exploration journey on the cloud.

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Posted by crazydip on Mon, 11 Mar 2019 01:51:25 -0700

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