sql-server-samples/samples/features/sql2019notebooks/OneTrillionRowsWarm.ipynb

Blazing fast performance on 1 Trillion Rows

Environment Details
SQL Server 2019
Windows Server 2016
8-Socket (224 cores, 12TB RAM and 200TB+ SSD storage) Lenovo Server (ThinkSystem SR950) using Intel Cascade Lake processors

This query runs a TPC-H query on a table with 1 trillion rows.

In [1]:

select 
    SERVERPROPERTY('Edition') as Edition, 
    SERVERPROPERTY('ProductVersion') as ProductVersion, 
    (physical_memory_kb/(1024*1024)) as [Physical Memory (GB)], 
    cpu_count as [CPU Count], cores_per_socket [Cores Per Socket], 
    numa_node_count as [Numa Node Count], 
    socket_count [Socket Count] 
from sys.dm_os_sys_info

Out [1]:

(1 row affected)

Total execution time: 00:00:00.010

Edition	ProductVersion	Physical Memory (GB)	CPU Count	Cores Per Socket	Numa Node Count	Socket Count
Enterprise Edition (64-bit)	15.0.1800.32	12287	448	28	8	8

Query Execution (Warm Cache)

Executing the query against a trillion rows

In [3]:

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_BIG(*)					AS COUNT_ORDER
FROM	LINEITEM
WHERE	L_SHIPDATE	<= dateadd(dd, -84, cast('1998-12-01'as date))
GROUP	BY	L_RETURNFLAG,
		L_LINESTATUS
ORDER	BY	L_RETURNFLAG,
		L_LINESTATUS

Out [3]:

(4 rows affected)

Total execution time: 00:01:49.055

L_RETURNFLAG	L_LINESTATUS	SUM_QTY	SUM_BASE_PRICE	SUM_DISC_PRICE	SUM_CHARGE	AVG_QTY	AVG_PRICE	AVG_DISC	COUNT_ORDER
A	F	6607498422967.00	9907944790073789.01	9412534887542805.5029	9789033542413688.460306	25.499849	38237.027384	0.050001	259119117459
N	F	172490750754.00	258648998956769.81	245716194671224.9925	255546008060751.851842	25.500349	38237.643650	0.050004	6764250468
N	O	13059206961084.00	19582291240784926.26	18603181042211704.5621	19347316948124666.963125	25.500049	38237.344944	0.049999	512124763608
R	F	6607437171988.00	9907852600116816.38	9412459553931927.4868	9788956809985580.060997	25.499869	38237.056271	0.049999	259116510688

Execution statistics

Table 'LINEITEM'. Scan count 789, logical reads 3530482, physical reads 0, page server reads 0, read-ahead reads 0, page server read-ahead reads 0, lob logical reads 706634933, lob physical reads 0, lob page server reads 0, lob read-ahead reads 0, lob page server read-ahead reads 0.

Table 'LINEITEM'. Segment reads 1504451, segment skipped 0.

Table 'Worktable'. Scan count 0, logical reads 0, physical reads 0, page server reads 0, read-ahead reads 0, page server read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob page server reads 0, lob read-ahead reads 0, lob page server read-ahead reads 0.

Read Throughput for LOB logical reads: 49Gb/sec

Rows processed per second: 9,633,026,529 rows/sec (Over 9 billion rows per second)

Task Manager screenshot while query is being executed

In [2]:

from IPython.display import Image
Image(filename="OneTrillionRowsTaskManager.png")

Out [2]:

Table Details

LINEITEM

RAW DATA: ~146 TB

COMPRESSED DATA SIZE: ~54 TB

ROWS: 1,049,999,891,699

In [4]:

from IPython.display import Image
Image(filename="TableStorage.png")

Out [4]: