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对文件进行查询
目前，我们支持 Parquet、CSV、ORC 和 NDJson 格式文件的查询。
以 Taxi Zone Lookup Table 数据为例。
1. curl "https://d37ci6vzurychx.cloudfront.net/misc/taxi+_zone_lookup.csv" -o /tmp/taxi+_zone_lookup.csv
创建一个外部表：
1. CREATE EXTERNAL TABLE taxi_zone_lookup with (location='/tmp/taxi+_zone_lookup.csv',format='csv');
检查外部表的组织和结构：
1. DESC TABLE taxi_zone_lookup;
1. +--------------------+----------------------+------+------+--------------------------+---------------+
2. | Column | Type | Key | Null | Default | Semantic Type |
3. +--------------------+----------------------+------+------+--------------------------+---------------+
4. | LocationID | Int64 | | YES | | FIELD |
5. | Borough | String | | YES | | FIELD |
6. | Zone | String | | YES | | FIELD |
7. | service_zone | String | | YES | | FIELD |
8. | greptime_timestamp | TimestampMillisecond | PRI | NO | 1970-01-01 00:00:00+0000 | TIMESTAMP |
9. +--------------------+----------------------+------+------+--------------------------+---------------+
10. 4 rows in set (0.00 sec)
注意
在这里，你可能会注意到出现了一个 greptime_timestamp 列，这个列作为表的时间索引列，在文件中并不存在。这是因为在创建外部表时，我们没有指定时间索引列，greptime_timestamp 列被自动添加作为时间索引列，并且默认值为 1970-01-01 00:00:00+0000。你可以在 create 文档中查找更多详情。
现在就可以查询外部表了：
1. SELECT `Zone`, `Borough` FROM taxi_zone_lookup LIMIT 5;
1. +-------------------------+---------------+
2. | Zone | Borough |
3. +-------------------------+---------------+
4. | Newark Airport | EWR |
5. | Jamaica Bay | Queens |
6. | Allerton/Pelham Gardens | Bronx |
7. | Alphabet City | Manhattan |
8. | Arden Heights | Staten Island |
9. +-------------------------+---------------+
对目录进行查询
首先下载一些数据：
1. mkdir /tmp/external
2. curl "https://d37ci6vzurychx.cloudfront.net/trip-data/yellow_tripdata_2022-01.parquet" -o /tmp/external/yellow_tripdata_2022-01.parquet
3. curl "https://d37ci6vzurychx.cloudfront.net/trip-data/yellow_tripdata_2022-02.parquet" -o /tmp/external/yellow_tripdata_2022-02.parquet
验证下载情况：
1. ls -l /tmp/external
2. total 165368
3. -rw-r--r-- 1 wenyxu wheel 38139949 Apr 28 14:35 yellow_tripdata_2022-01.parquet
4. -rw-r--r-- 1 wenyxu wheel 45616512 Apr 28 14:36 yellow_tripdata_2022-02.parquet
创建外部表
1. CREATE EXTERNAL TABLE yellow_tripdata with(location='/tmp/external/',format='parquet');
执行查询：
1. SELECT count(*) FROM yellow_tripdata;
1. +-----------------+
2. | COUNT(UInt8(1)) |
3. +-----------------+
4. | 5443362 |
5. +-----------------+
6. 1 row in set (0.48 sec)
1. SELECT * FROM yellow_tripdata LIMIT 5;
1. +----------+----------------------+-----------------------+-----------------+---------------+------------+--------------------+--------------+--------------+--------------+-------------+-------+---------+------------+--------------+-----------------------+--------------+----------------------+-------------+---------------------+
2. | VendorID | tpep_pickup_datetime | tpep_dropoff_datetime | passenger_count | trip_distance | RatecodeID | store_and_fwd_flag | PULocationID | DOLocationID | payment_type | fare_amount | extra | mta_tax | tip_amount | tolls_amount | improvement_surcharge | total_amount | congestion_surcharge | airport_fee | greptime_timestamp |
3. +----------+----------------------+-----------------------+-----------------+---------------+------------+--------------------+--------------+--------------+--------------+-------------+-------+---------+------------+--------------+-----------------------+--------------+----------------------+-------------+---------------------+
4. | 1 | 2022-02-01 00:06:58 | 2022-02-01 00:19:24 | 1 | 5.4 | 1 | N | 138 | 252 | 1 | 17 | 1.75 | 0.5 | 3.9 | 0 | 0.3 | 23.45 | 0 | 1.25 | 1970-01-01 00:00:00 |
5. | 1 | 2022-02-01 00:38:22 | 2022-02-01 00:55:55 | 1 | 6.4 | 1 | N | 138 | 41 | 2 | 21 | 1.75 | 0.5 | 0 | 6.55 | 0.3 | 30.1 | 0 | 1.25 | 1970-01-01 00:00:00 |
6. | 1 | 2022-02-01 00:03:20 | 2022-02-01 00:26:59 | 1 | 12.5 | 1 | N | 138 | 200 | 2 | 35.5 | 1.75 | 0.5 | 0 | 6.55 | 0.3 | 44.6 | 0 | 1.25 | 1970-01-01 00:00:00 |
7. | 2 | 2022-02-01 00:08:00 | 2022-02-01 00:28:05 | 1 | 9.88 | 1 | N | 239 | 200 | 2 | 28 | 0.5 | 0.5 | 0 | 3 | 0.3 | 34.8 | 2.5 | 0 | 1970-01-01 00:00:00 |
8. | 2 | 2022-02-01 00:06:48 | 2022-02-01 00:33:07 | 1 | 12.16 | 1 | N | 138 | 125 | 1 | 35.5 | 0.5 | 0.5 | 8.11 | 0 | 0.3 | 48.66 | 2.5 | 1.25 | 1970-01-01 00:00:00 |
9. +----------+----------------------+-----------------------+-----------------+---------------+------------+--------------------+--------------+--------------+--------------+-------------+-------+---------+------------+--------------+-----------------------+--------------+----------------------+-------------+---------------------+
10. 5 rows in set (0.11 sec)
注意
查询结果中包含 greptime_timestamp 列的值，尽管它在原始文件中并不存在。这个列的所有值均为 1970-01-01 00:00:00+0000，这是因为我们在创建外部表时，自动添加列 greptime_timestamp，并且默认值为 1970-01-01 00:00:00+0000。你可以在 create 文档中查找更多详情。
