Try out parallel import and data compression

This topic describes parallel import and data compression.

Parallel import

Apart from analytical queries, operational OLAP involves large-scale data import in batches. OceanBase Database's parallel execution framework allows DML statements to be executed in parallel (parallel DML), enabling concurrent writes across servers for a multi-node database while ensuring the consistency of large transactions. The asynchronous minor compaction optimizes the performance of the LSM-tree-based storage engine in handling large transactions when memory is tight.

Try out PDML: Starting from the TPC-H lineitem table, create an empty table named lineitem2 with the same schema. Then use an INSERT INTO ... SELECT statement to insert all 6 million rows from the lineitem table to the lineitem2 table. Perform the following operations to observe the results and differences.

First, copy the schema of the lineitem table to create the lineitem2 table. Note that in OceanBase Database, you can scale out a table by partition. In this example, the lineitem2 table also has 16 partitions:

obclient [test]>  SHOW CREATE TABLE lineitem\G
*************************** 1. row ***************************
       Table: lineitem

Create Table: CREATE TABLE `lineitem` (
  `l_orderkey` bigint(20) NOT NULL,
  `l_partkey` bigint(20) NOT NULL,
  `l_suppkey` bigint(20) NOT NULL,
  `l_linenumber` bigint(20) NOT NULL,
  `l_quantity` bigint(20) NOT NULL,
  `l_extendedprice` bigint(20) NOT NULL,
  `l_discount` bigint(20) NOT NULL,
  `l_tax` bigint(20) NOT NULL,
  `l_returnflag` char(1) DEFAULT NULL,
  `l_linestatus` char(1) DEFAULT NULL,
  `l_shipdate` date NOT NULL,
  `l_commitdate` date DEFAULT NULL,
  `l_receiptdate` date DEFAULT NULL,
  `l_shipinstruct` char(25) DEFAULT NULL,
  `l_shipmode` char(10) DEFAULT NULL,
  `l_comment` varchar(44) DEFAULT NULL,
  PRIMARY KEY (`l_orderkey`, `l_linenumber`),
  KEY `I_L_ORDERKEY` (`l_orderkey`) BLOCK_SIZE 16384 LOCAL,
  KEY `I_L_SHIPDATE` (`l_shipdate`) BLOCK_SIZE 16384 LOCAL
) DEFAULT CHARSET = utf8mb4 ROW_FORMAT = COMPACT COMPRESSION = 'zstd_1.3.8' REPLICA_NUM = 1 BLOCK_SIZE = 16384 USE_BLOOM_FILTER = FALSE TABLET_SIZE = 134217728 PCTFREE = 0 TABLEGROUP = 'x_tpch_tg_lineitem_order_group'
 partition by key(l_orderkey)
  (partition p0,
  partition p1,
  partition p2,
  partition p3,
  partition p4,
  partition p5,
  partition p6,
  partition p7,
  partition p8,
  partition p9,
  partition p10,
  partition p11,
  partition p12,
  partition p13,
  partition p14,
  partition p15)
1 row in set

Perform the insertion without enabling PDML

After the lineitem2 table is created, insert the data without enabling PDML. Since this is a large transaction involving 6 million rows, increase the default transaction timeout period of OceanBase Database (in μs):

# SET ob_query_timeout = 1000000000;  
# SET ob_trx_timeout = 1000000000;  

The execution result is as follows:

obclient [test]> INSERT INTO lineitem2 SELECT * FROM lineitem;
Query OK, 6001215 rows affected (1 min 47.312 sec)
Records: 6001215  Duplicates: 0  Warnings: 0

As we can see, it takes 107 seconds for OceanBase Database to insert 6 million rows in a transaction when PDML is disabled.

Enable PDML for the insertion

Add a hint to enable PDML. Note that before you insert the data, clear the data inserted last time.

obclient [test]> TRUNCATE TABLE lineitem2;
obclient [test]> INSERT /*+ parallel(16) enable_parallel_dml */ INTO lineitem2 SELECT * FROM lineitem;

Check the execution time:

obclient> TRUNCATE TABLE lineitem2;
Query OK, 0 rows affected (0.108 sec)

obclient> INSERT /*+ parallel(16) enable_parallel_dml */ INTO lineitem2 SELECT * FROM lineitem;
Query OK, 6001215 rows affected (22.117 sec)
Records: 6001215  Duplicates: 0  Warnings: 0

As we can see, with PDML enabled, OceanBase Database takes about 22 seconds to insert 6 million rows in a transaction. PDML improves the performance by about 5 times. This feature helps users who need to process batch data.

Data compression

OceanBase Database has developed its own storage engine based on the LSM-tree structure. In this architecture, data is divided into baseline data (SSTable) and incremental data (MemTable). The baseline data is stored on disk, and incremental modifications are stored in memory. This way, the data on disk can be stored in a more compact format. In addition, because the baseline data on disk is not frequently updated, OceanBase Database uses general compression algorithms to compress the baseline data again, achieving a high compression ratio. The data write and query performance is not compromised. This compression mechanism applies to both data imported from external sources and data generated within OceanBase Database. The following describes how to import a large amount of external data and observe the compression ratio of the data in OceanBase Database.

Data preparation

First, use the data preparation tool CreateData.jar to generate 50 million rows of simulated data to the /home/soft directory. The data generation process may take several minutes. You can also use other tools to generate test data.

#mkdir /home/soft/
#java -jar CreateData.jar /home/soft/ 50000000
filePath is : /home/soft/
Start Time : 2022-07-10 15:33:00
End Time : 2022-07-10 15:52:53
#du -sh *
10G     t_bigdata_loader.unl

OceanBase Database allows you to import data in CSV format to the database in various ways. This topic introduces how to import data by using the LOAD DATA statement.

1. Name the generated files and verify their sizes.

   # mv t_bigdata_loader.unl t_f1.csv
   # du -sh t_f1.csv
   10G     t_f1.csv
   

2. View the content of the t_f1.csv file. You will find that the random algorithm in the pre-generated CSV file has obtained 8 columns of data that correspond to different data types. Therefore, before you explore the data compression feature of OceanBase Database, create a table in the tenant and import the records in the CSV file to the table.

   1|1896404182|1980-06-01|2004-10-25 13:30:39|7470.689|33062564.9527|nOLqnBYtnp|BzWYjZjeodtBNzXSMyBduMNzwDPSiVmhVgPJMeEkeAwKBCorzblwovIHDKBsQhbVjQnIdoeTsiLXTNwyuAcuneuNaol|
   2|572083440|2018-11-09|1998-07-11 01:23:28|6891.054|66028434.4013|UzqteeMaHP|vQWbWBXEWgUqUTzqsOSciiOuvWVcZSrlEOQDwDVGmvGRQYWmhCFdEkpsUsqrWEpKtmxSwURHIHxvmlXHUIxmfelYboeGEuScKKqzpuNLryFsStaFTTRqSsVlCngFFjHnEnpaCnWsdwztbiHJyoGkaxrFmyPAmVregfydArrUZsgRqBpQ|
   3|1139841892|2006-10-07|1999-06-26 17:02:22|286.43692|51306547.5055|KJJtylgxkv|BuBdFTBIIFsEPVxsVBRqAnFXSBdtZDgfumUhIx|
   4|1777342512|1982-12-18|2017-11-19 07:56:35|2986.242|85860387.8696|rTkUBWhdPt|JSazOTAmvtCBrINttDwublNJNRFDIiWkHtWZXmWgKHoZCKGqmmETkIcYLXiSgKkoaATNgjvPxVGjeCOODLEWqrQHqowbMjOLOKrtirWEOpUSxiUudZduTCUvZElKzZfggvCBNthwzKJc|
   ....
   

3. In the test tenant and test database, create a table named t_f1. For more information, see the topic on Creating a tenant.

Data import

You can use the Load Data statement in OceanBase Database to import data. Load Data also supports parallel import. Before you import data, perform the following setup. The Load Data statement supports importing data files only from the local disk of the OBServer node. If you want to import data remotely, you can use the obloader tool.

obclient [test]> SET GLOBAL secure_file_priv = "/";
obclient [test]> GRANT FILE ON *.* to username;

After the setup is completed, reconnect the session to take effect. Then set the transaction timeout period of the session again to ensure that it does not time out during the execution.

obclient [test]> SET ob_query_timeout=1000000000;
obclient [test]> SET ob_trx_timeout=1000000000;

Then run the import statement:

obclient [test]> LOAD DATA /*+ parallel(16) */ INFILE '/home/soft/t_f1.csv' INTO table t_f1 fields TERMINATED BY '\|' LINES TERMINATED BY '\n';

As you can see, with parallel import enabled, it takes about 4 minutes to import 10 GB of data. The CPU parallelism for the tenant in this topic is set to 16. You can set an appropriate parallelism level based on your configuration. Higher parallelism leads to faster import.

After the import is completed, query the number of records and the occupied space size in the table.

1. Query that the table contains 50 million records.

   obclient [test]> SELECT COUNT(*) FROM t_f1;
   +----------+
   | count(*) |
   +----------+
   | 50000000 |
   +----------+
   

2. Perform a major compaction.

   Log in to the sys tenant of the cluster as the root user and trigger a major compaction to compress the incremental data and baseline data together. You can also manually trigger a compaction by using the following method.

   # obclient -h127.0.0.1 -P2881 -uroot@sys  -Doceanbase -A -p -c
   obclient[oceanbase]> ALTER SYSTEM MAJOR FREEZE;
   

3. Query the state of the compaction. When the following query returns IDLE, the compaction is completed.

   obclient [oceanbase]> SELECT * FROM oceanbase.CDB_OB_MAJOR_COMPACTION;
   +-----------+---------------------+----------------------------+----------------------+---------------------+----------------------------+----------------------------+--------+----------+--------------+------+
   | TENANT_ID | FROZEN_SCN          | FROZEN_TIME                | GLOBAL_BROADCAST_SCN | LAST_SCN            | LAST_FINISH_TIME           | START_TIME                 | STATUS | IS_ERROR | IS_SUSPENDED | INFO |
   +-----------+---------------------+----------------------------+----------------------+---------------------+----------------------------+----------------------------+--------+----------+--------------+------+
   |         1 | 1679248800404017149 | 2023-03-20 02:00:00.404017 |  1679248800404017149 | 1679248800404017149 | 2023-03-20 02:00:44.035785 | 2023-03-20 02:00:00.442481 | IDLE   | NO       | NO           |      |
   |      1001 | 1679248804191204504 | 2023-03-20 02:00:04.191205 |  1679248804191204504 | 1679248804191204504 | 2023-03-20 02:00:46.094551 | 2023-03-20 02:00:04.218608 | IDLE   | NO       | NO           |      |
   |      1002 | 1679248802450394471 | 2023-03-20 02:00:02.450394 |  1679248802450394471 | 1679248802450394471 | 2023-03-20 02:00:33.818514 | 2023-03-20 02:00:02.484814 | IDLE   | NO       | NO           |      |
   1 row in set
   

4. Query the following statement in the sys tenant to check the data storage usage after the data is imported to OceanBase Database.

   obclient [oceanbase]> select b.table_name,a.svr_ip,data_size/1024/1024/1024 from CDB_OB_TABLET_REPLICAS a,CDB_OB_TABLE_LOCATIONS b where a.tablet_id=b.tablet_id and b.table_name='T_F1';
   +------------+---------------+----------------------------+
   | table_name | svr_ip        | a.data_size/1024/1024/1024 |
   +------------+---------------+----------------------------+
   | t_f1       | xxx.xx.xxx.xx |             6.144531250000 |
   +------------+---------------+----------------------------+
   

The size of the compressed table is approximately 6.145 GB, and the compression ratio is 10/6.145 = 1.62.