Query External Data

Query on a file

Currently, we support queries on Parquet, CSV, ORC, and NDJson format file(s).

We use the Taxi Zone Lookup Table data as an example.

  1. curl "https://d37ci6vzurychx.cloudfront.net/misc/taxi+_zone_lookup.csv" -o /tmp/taxi+_zone_lookup.csv

Create an external table:

  1. CREATE EXTERNAL TABLE taxi_zone_lookup with (location='/tmp/taxi+_zone_lookup.csv',format='csv');

You can check the schema of the external table like follows:

  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)

Query External Data - 图1Note

Here, you may notice there is a greptime_timestamp column, which doesn’t exist in the file. This is because when creating an external table, if we didn’t specify a TIME INDEX column, the greptime_timestamp column is automatically added as the TIME INDEX column with a default value of 1970-01-01 00:00:00+0000. You can find more details in the create document.

Now you can query on the external table:

  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. +-------------------------+---------------+

Query on a directory

Let’s download some data:

  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

Verify the download:

  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

Create the external table:

  1. CREATE EXTERNAL TABLE yellow_tripdata with(location='/tmp/external/',format='parquet');

Run queries:

  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)

Query External Data - 图2Note

The query result includes the value of the greptime_timestamp column, although it does not exist in the original file. All these column values are 1970-01-01 00:00:00+0000, because when we create an external table, the greptime_timestamp column is automatically added with a default value of 1970-01-01 00:00:00+0000. You can find more details in the create document.