如何在配置单元中的分区数据中创建表？

时间：2018-03-29 11:44:14

标签： apache hive create-table hive-partitions

drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:16 / kylin / retailer / qi_basket_brand_bucket_fact / _impala_insert_staging drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:18 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI [mgupta @ sjc-dev-binn01~] $ hadoop fs -ls / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI 找到27项 drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:16 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201601 drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:16 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201602 drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:16 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201603 drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:16 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201604 drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:16 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201605 drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:16 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201606 drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:16 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201607 drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:16 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201608 drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:17 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201609 drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:17 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201610 drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:17 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201611 drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:17 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201612 drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:17 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201701 drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:17 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201702 drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:17 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201703 drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:17 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201704 drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:17 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201705 drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:17 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201706 drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:17 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201707 drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:18 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201708 drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:18 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201709 drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:18 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201710 drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:18 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201711 drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:18 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201712 drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:18 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201801 drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:18 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201802 drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:18 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201803 [mgupta @ sjc-dev-binn01~] $ hadoop fs -ls / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201601 找到3项 drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:16 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201601 / company_sid = 0 drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:16 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201601 / company_sid = 38527 drwxr-xr-x - mgupta supergroup 0 2018-03-26 22:16 / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201601 / company_sid = HIVE_DEFAULT_PARTITION [mgupta @ sjc-dev-binn01~] $ hadoop fs -ls / kylin / retailer / qi_basket_brand_bucket_fact / product_hierarchy_type = CI / month_id = 201601 / company_sid = 0 找到1项 -rw-r - r-- 3 mgupta supergroup 2069014 2018-03-26 22:16 /kylin/retailer/qi_basket_brand_bucket_fact/product_hierarchy_type=CI/month_id=201601/company_sid=0/f9466a0068b906cf-6ace7f8500000049_294515768_data.0.parq [mgupta @ sjc-dev-binn01~] $

2 个答案:

答案 0 :(得分：1)

您可以尝试以下步骤。

方法1

  1. 确定架构（列名称和类型 - 包括分区列）
  2. 创建一个配置单元分区表（确保添加分区列和分隔符信息）

  3. 将数据加载到分区表中。

    create table <table_name> (col1 data_type1, col2 data_type2..)
partitioned by(part_col data_type3)
row format delimited
fields terminated by '<field_delimiter_in_your_data>'

load data inpath '/hdfs/loc/file1' into table <table_name>
partition (<part_col>='201601');

load data inpath '/hdfs/loc/file1' into table <table_name>
partition (<part_col>='201602')

load data inpath '/hdfs/loc/file1' into table <table_name>
partition (<part_col>='201603')

    依此类推。

    4. 方法2

    1. 使用与主表相同的模式创建临时表（临时表），但不包含任何分区
    2. 将您的整个数据加载到此表格中（确保您拥有＆＃39; 分区列＆＃39;作为这些文件中的某个字段）

    3. 使用动态分区插入从登台表加载数据到主表。

      create table <staging_table> (col1 data_type1, col2 data_type2..)
row format delimited
fields terminated by '<field_delimiter_in_your_data>'

create table <main_table> (col1 data_type1, col2 data_type2..)
partitioned by(part_col data_type3);

load data inpath '/hdfs/loc/directory/' into table <staging_table>;

SET hive.exec.dynamic.partition=true; 
SET hive.exec.dynamic.partition.mode=nonstrict;

insert into table <main_table> 
partition(part_col) 
select col1,col2,....part_col from <staging_table>;

      4. 方法2的主要方面是：

      • 制作＆＃39; part_col ＆＃39;作为加载文件中的字段提供
      • 在最终的插入声明中，获取＆＃39; part_col ＆＃39;作为select子句的最后一个字段。

答案 1 :(得分：0)

让我们创建一个表，在年和月上有一个分区，表中有一个时间戳：

CREATE TABLE `mypart_p`(
   `id` bigint, 
   `open_ts` string 
)
PARTITIONED BY (YEAR INT, MONTH INT)

现在我必须改变表格。

ALTER TABLE mypart_p ADD PARTITION (YEAR=2020, MONTH=1)

我必须每年和每月都这样做，在 python 中循环执行。现在让我们用数据填充它并指定该数据属于哪个分区：

INSERT into mypart_p PARTITION (YEAR=2020, MONTH=1)

select id,
open_ts

FROM some_other_table

WHERE substring(open_ts,0,4) = '2020'
AND substring(open_ts,6,2) = '01'
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