Perth APAC Groundbreakers tour - 18c features

Copyright © 2018, Oracle and/or its affiliates. All rights reserved.
Connor McDonald

Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |
2

3

Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |
Stuff
youtube bit.ly/youtube-connor
blog bit.ly/blog-connor
twitter bit.ly/twitter-connor
400+ posts mainly on database & development
250 technical videos, new uploads every week
rants and raves on tech and the world :-)

Copyright © 2018, Oracle and/or its affiliates. All rights reserved.
etc...
facebook bit.ly/facebook-connor
linkedin bit.ly/linkedin-connor
instagram bit.ly/instagram-connor
slideshare bit.ly/slideshare-connor

https://asktom.oracle.com

7https://asktom.oracle.com/officehours

150 hours of free access (so far)
8

Cool stuff about 12.2/18c/19c
Connor McDonald
Developer Advocate

"Whoa....hold on!"
10

12c, 13, 14, 15, 16, 17, 18c
11
?

18c = 12.2.0.2
12
MOS 2285040.1

19c = 12.2.0.3
13

Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | 14
why me ?

why you ?

12.2!18!
12.2!12.2!
18!

reality
22

SQL> select * from v$version;
BANNER
----------------------------------------------------------
Oracle8i Enterprise Edition Release 8.1.7.4.0 - Production
PL/SQL Release 8.1.7.4.0 - Production
CORE 8.1.7.0.0 Production
TNS for HPUX: Version 8.1.7.4.0 - Production
NLSRTL Version 3.4.1.0.0 - Production

BANNER
----------------------------------------------------------

you still should be here
27

there's a lot in 12.2/18/19

get started right now

install nothing

https://cloud.oracle.com/tryit

install a little bit

https://tinyurl.com/ora18vm

install lots :-)

http://www.oracle.com/technetwork/database/enterprise-edition/downloads/index.html

18c install lots :-)

coming soon

install lots :-)

1) gold image service

2) read-only ORACLE_HOME

3) Oracle database in Docker
https://tinyurl.com/ora18docker

because there's 19c stuff in here

Safe Harbor Statement
The following is intended to outline our general product direction. It is intended for
information purposes only, and may not be incorporated into any contract. It is not a
commitment to deliver any material, code, or functionality, and should not be relied upon
in making purchasing decisions. The development, release, and timing of any features or
functionality described for Oracle’s products remains at the sole discretion of Oracle.
46

licensing

UNZIP INSTALL
RPM INSTALL
DOCKER
READ-ONLY
GOLD IMAGE

external tables

ext_emp

SQL> create table ext_emp (
2 empno number(4),
3 ename varchar2(10),
4 job varchar2(9),
5 mgr number(4),
6 hiredate date,
7 sal number(7,2),
8 comm number(7,2),
9 deptno number(2)
10 )
11 organization external
12 ( type oracle_loader
13 default directory TMP
14 access parameters
15 ( records delimited by newline
16 fields terminated by ','
17 missing field values are null
18 ( empno,ename,job,mgr,hiredate,sal,comm,deptno )
19 )
20 location ('emp20161001.dat'));
Table created.

SQL> select * from ext_emp;
select * from ext_emp
*
ERROR at line 1:
ORA-29913: error in executing ODCIEXTTABLEFETCH callout
ORA-30653: reject limit reached

easy fix

SQL> create table ext_emp (
2 empno number(4),
...
18 ( empno,ename,job,mgr,hiredate,sal,comm,deptno )
19 )
20 location ('emp20161001.dat'))
21 REJECT LIMIT UNLIMITED;
Table created.

12.2

query time modification

SQL> select * from ext_emp
2 external modify ( reject limit unlimited );
EMPNO ENAME JOB MGR HIREDATE SAL
---------- ---------- --------- ---------- --------- ---------- ---
7499 ALLEN SALESMAN 7698 20-FEB-81 1600
7521 WARD SALESMAN 7698 22-FEB-81 1250
7566 JONES MANAGER 7839 02-APR-81 2975
...
7902 FORD ANALYST 7566 03-DEC-81 3000
7934 MILLER CLERK 7782 23-JAN-82 1300
13 rows selected.

SQL> select * from ext_emp
2 external modify ( location ('emp20161002.dat') );
EMPNO ENAME JOB MGR HIREDATE SAL
---------- ---------- --------- ---------- --------- ---------- ---
7902 FORD ANALYST 7566 03-DEC-81 3000
7934 MILLER CLERK 7782 23-JAN-82 1300
7566 JONES MANAGER 7839 02-APR-81 2975
...
7499 ALLEN SALESMAN 7698 20-FEB-81 1600
7521 WARD SALESMAN 7698 22-FEB-81 1250
8 rows selected.

select * from ext_tab external modify (
[ default directory ]
[ location ]
[ access parameters ]
[ reject limit ]
);

18c

zero ddl option

SQL> select * from external (
2 empno number(4),
3 ename varchar2(10),
4 ...
18 ( empno,ename,job,mgr,...)
19 )
20 location ('emp20161001.dat')
21 );

polymorphic table functions

recap: table functions

SQL> create or replace
2 type MY_OBJECT (
3 empno number(4),
4 ename varchar2(10)
...
10 /
Type created.
2 type OBJ_LIST as table of MY_OBJECT;
3 /
Type created.

2 function MY_PIPE_FUNC return OBJ_LIST pipelined as
...
...
pipe row ( obj_list(v_empno, v_ename, ... ));
...
64 end;
65 /
Function created.

SQL> select * from table(my_pipe_func);
EMPNO ENAME JOB
---------- ---------- ---------
7369 SMITH CLERK
7499 ALLEN SALESMAN
7521 WARD SALESMAN
7566 JONES MANAGER
7654 MARTIN SALESMAN
7698 BLAKE MANAGER
7782 CLARK MANAGER
7788 SCOTT ANALYST
my_pipe_func();

static return type
2 type MY_OBJECT (
3 empno number(4),
4 ename varchar2(10)
...
10 /

polymorphic table functions

"hack" into SQL processing

2 package MY_PKG as
3 --
4 -- description phase
5 --
6 function describe (
7 tab in out dbms_tf.table_t,
8 ...
9 ) return dbms_tf.describe_t;
10
11 --
12 -- fetch phase
13 --
14 procedure fetch_rows (col_names varchar2);
15 end ;

example

2 package row_num_p is
3 function describe(tab in out dbms_tf.table_t)
4 return dbms_tf.describe_t;
5
6 procedure fetch_rows;
7 end;
8 /
Package created.

2 package body row_num_p is
3 function describe(tab in out dbms_tf.table_t)
4 return dbms_tf.describe_t as
5 begin
6 return
7 dbms_tf.describe_t(
8 new_columns =>
9 dbms_tf.columns_new_t(
10 1=>dbms_tf.column_metadata_t(
11 name => 'ROW_ID',
12 type => dbms_tf.type_number)));
13 end;
14

14
15 procedure fetch_rows is
16 row_cnt constant pls_integer := dbms_tf.get_env().row_count;
17 col dbms_tf.tab_number_t;
18 begin
19 for i in 1 .. row_cnt
20 loop
21 col(i) := i;
22 end loop;
23 dbms_tf.put_col(1, col);
24 end;
25
26 END;
27 /
Package body created.

2 function row_num(tab table) return table
3 pipelined table polymorphic using row_num_p;
4 /
Function created.

SQL> select * from row_num(scott.dept);
DEPTNO DNAME LOC ROW_ID
---------- -------------- ------------- ----------
10 ACCOUNTING NEW YORK 1
20 RESEARCH DALLAS 2
30 SALES CHICAGO 3
40 OPERATIONS BOSTON 4
SQL> select * from row_num(scott.salgrade);
GRADE LOSAL HISAL ROW_ID
---------- ---------- ---------- ----------
1 700 1200 1
2 1201 1400 2
3 1401 2000 3
4 2001 3000 4
5 3001 9999 5

any table

SQL> with MY_TAB as
2 ( select empno, ename
3 from scott.emp
4 )
5 select * from row_num(my_tab);
EMPNO ENAME ROW_ID
---------- ---------- ----------
7369 SMITH 1
7499 ALLEN 2
7521 WARD 3
7566 JONES 4
7654 MARTIN 5
7698 BLAKE 6
7782 CLARK 7
7788 SCOTT 8
7839 KING 9
...

very extensible

2 package csv_pkg as
3
4 function describe (
6 col_names varchar2
7 ) return dbms_tf.describe_t;
8
9 procedure fetch_rows (col_names varchar2);
10 end csv_pkg;
11 /
Package created.

2 package body csv_pkg as
3 function describe(
5 col_names varchar2 ) return dbms_tf.describe_t as
6 new_cols dbms_tf.columns_new_t;
7 col_id pls_integer := 2;
8 begin
9 tab.column(1).pass_through := FALSE;
10 tab.column(1).for_read := TRUE;
11 new_cols(1) := tab.column(1).description;
12
13 for j in 1 .. ( length(col_names) - length(replace(col_names,',')) ) + 1
14 loop
15 new_cols(col_id) := dbms_tf.column_metadata_t(
16 name=>regexp_substr(col_names, '[^,]+', 1, j),
17 type=>dbms_tf.type_varchar2
18 );
19 col_id := col_id + 1;
20 end loop;
21
22 return dbms_tf.describe_t( new_columns => new_cols );
23 end;

25 procedure fetch_rows (col_names varchar2) as
26 rowset dbms_tf.row_set_t;
27 row_count pls_integer;
28 begin
29 dbms_tf.get_row_set(rowset, row_count => row_count);
30
31 for i in 1 .. row_count loop
32 for j in 2 .. ( length(col_names) - length(replace(col_names,',')) ) + 2
33 loop
34 rowset(j).tab_varchar2(i) :=
35 regexp_substr(rowset(1).tab_varchar2(i), '[^,]+', 1, j - 1);
36 end loop;
37 end loop;
38
39 dbms_tf.put_row_set(rowset);
40
41 end;
42
43 end csv_pkg;
44 /
Package body created.

SQL> create or replace function csv_to_columns(
2 tab table, col_names varchar2
3 ) return table pipelined row polymorphic using csv_pkg;
4 /
Function created.
SQL> with csvs as (
2 select 'two,comma-separated values' str from dual
3 )
4 select *
5 from csv_to_columns( csvs, 'c1,c2' );
STR C1 C2
-------------------------- ---------- -----------------------
two,comma-separated values two comma-separated values

livesql.oracle.com

qualified expressions

aka, full constructor support

good old days

SQL> declare
2 type my_rec is record
3 ( c1 int,
4 c2 date,
5 c3 varchar2(30),
6 c4 boolean
7 );
8
9 l_rec my_rec;
10 begin
11 l_rec.c1 := 10;
12 l_rec.c2 := sysdate;
13 l_rec.c3 := 'Lots of typing';
14 l_rec.c4 := true;
15 end;
16 /
PL/SQL procedure successfully completed.

18c+

SQL> declare
2 type my_rec is record
3 ( c1 int,
4 c2 date,
5 c3 varchar2(30),
6 c4 boolean
7 );
8
9 l_rec my_rec;
10 begin
11 l_rec := my_rec(c1=>10,
12 c2=>sysdate,
13 c3=>'Lots of typing',
14 c4=>true);
15 end;
16 /

arrays too

SQL> declare
2 type my_array is table of int
3 index by pls_integer;
4
5 l_array my_array;
6 begin
7 l_array :=
8 my_array(1=>123,
9 2=>456,
10 3=>789,
11 7=>1000);
12 end;
13 /

a nicer form of murder :-)

aka, #1 reason for upgrading to 18c

SQL> insert into MY_TABLE
2 select *
3 from MY_HUGE_GREAT_FAT_TABLE;
103

2 select *
3 from MY_HUGE_GREAT_FAT_TABLE
4 where LOAD_DATE > sysdate - 1;
105

SQL> alter system kill session '123,456' immediate
106

18c

SQL> alter system kill cancel sql '123,456';
108

maybe murder won't help

111

bad SQL just keeps coming back...

19c

automatic quarantine of bad SQL
elapsed time
resource consumption

error on subsequent execution

1) alerts to administrator

or...

2) automated historical diagnosis/repair

maybe murder wasn't the right thing

2 select *
121

2 select *
3 from MY_HUGE_GREAT_FAT_TABLE w
123
/*+ INDEX(W CUST_DATE_IX) */ *

18c

SQL> alter system set optimizer_ignore_hints = true
125

maybe it was the opposite ?

cool

2 select *
129

but what is best practice ?

1) monitor the SQL workload
AWR / Top SQL

2) consider indexes per SQL
leading columns

3) consolidate tables/columns
(a)
(a,b)
(a,b,c)

4) create nosegment/unusable
dictionary only

5) check "virtual" explain plan
cost/cardinality

6) create true index (as invisible)
no impact risk

7) test execute each SQL for benefit
response time/IO

8) decide on each index worth
"majority wins"

9) add NO_INDEX hint to others
no regression

10) make new indexes visible

we're done!

go to step 1

19c

automatic indexes

outages... suck

12.2

online "everything"

SQL> alter table t move online;
Table altered.

really is "everything"

SQL> alter table MY_SALES move
2 compress tablespace users
3 update indexes
4 (sales_ix1 tablespace indexes01,
5 sales_ix2 tablespace indexes02)
6 online;
Table altered.

partition existing table
one command

SQL> create table T as
2 select d.*
3 from dba_Objects d,
4 ( select 1 from dual
5 connect by level <= 20 )
6 where d.object_id is not null;
Table created.
SQL> create index IX on t ( object_id );
Index created.
SQL> create index IX2 on t ( created, object_name );
Index created.

SQL> alter table T modify
2 partition by range (object_id) interval (10000)
3 (
4 partition p1 values less than (20000)
5 ) online
6 including rows where created > date '2010-01-01'
7 update indexes
8 ( ix local tablespace new_idx_ts,
9 ix2 global partition by range (created)
10 (
11 partition ix2_p1 values less than (date '2016-08-01'),
12 partition ix2_p2 values less than (maxvalue)
13 )
14 );
Table altered.
compress

one thing missing

fixed in 18c

online merge partition

"big deal"

SQL> create table sales
2 ( ts timestamp,
3 id int,
4 amt number,
5 product int,
6 customer int,
...
...
17 )
18 partition by range ( ts )
19 interval ( numtodsinterval(1,'HOUR') )
20 (
21 partition p1 values less than ( timestamp '2018-07-01 00:00:00' )
22 );
Table created.

24 hours later

SQL> select partition_name, high_value
2 from user_tab_partitions
3 where table_name = 'SALES'
4 order by partition_position;
PARTITION_NAME HIGH_VALUE
------------------------------ -----------------------------------
P1 TIMESTAMP' 2018-07-01 00:00:00'
P20180701_00 TIMESTAMP' 2018-07-01 01:00:00'
P20180701_01 TIMESTAMP' 2018-07-01 02:00:00'
P20180701_02 TIMESTAMP' 2018-07-01 03:00:00'
P20180701_03 TIMESTAMP' 2018-07-01 04:00:00'
...
...
P20180702_13 TIMESTAMP' 2018-07-02 14:00:00'
P20180702_14 TIMESTAMP' 2018-07-02 15:00:00'
P20180702_15 TIMESTAMP' 2018-07-02 16:00:00'
41 rows selected.

SQL> select * from sales
2 where ts > timestamp '2018-07-02 15:00:00';
---------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Pstart| Pstop |
---------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 9 | 387 | 7 (0)| | |
| 1 | PARTITION RANGE ITERATOR| | 9 | 387 | 7 (0)| 41 |1048575|
|* 2 | TABLE ACCESS FULL | SALES | 9 | 387 | 7 (0)| 41 |1048575|
---------------------------------------------------------------------------------------

one year later ...

... lot of partitions

18c

SQL> declare
2 d date := date '2018-07-01';
3 ddl varchar2(4000);
4 begin
5 select listagg(partition_name||chr(10),',') within group ( order by partition_position )
6 into ddl
7 from user_tab_partitions
8 where table_name = 'SALES'
9 and partition_name like 'P'||to_char(d,'yyyymmdd')||'%';
10
11 ddl := 'alter table sales merge partitions '||ddl||
12 ' into partition p'||to_char(d,'yyyymmdd')||' online';
13
14 dbms_output.put_line(ddl);
15 execute immediate ddl;
16 end;
17 /
alter table sales merge partitions
P20180701_00
,P20180701_01
,P20180701_02
...
,P20180701_23
into partition p20180701 online

security

security ... is not easy :-(

Change sys password
Stop personal data exposure on users accounts
Secure access to dba role views
Check use of system tablespace as default
Create a role to manage users accounts
Secure access to catalog roles
Check that O7_dictionary_accessibility is set to false
Check that remote_listener is null
Make extproc secure
Review database accounts, ensuring they belong to business users.
Check core_dump_dest is valid
Audit utl_file_dir parameter
Remove oo4o if not needed
Check that global_names is true
Check that max_enabled_roles is set correctly
Audit dbms_backup_restore package permissions
Check user_dump_dest is valid
Password protect admin roles
Disable remote login password file
Use obfuscated naming convention for users accounts
Secure ALL_USERS view
Audit known default role passwords
Lock dormant database accounts and remove after time delay
Audit users accounts for weak passwords
Use proxy authentication to help resolve SSO issues
Audit Java access to the OS
Add password management for default accounts
Change system password
Check that remote_os_roles is set to false
Audit use of IFILE

DBSAT

[oracle@host122]$ ./dbsat collect system/****** /tmp/dbsat_collect
...
Connecting to the target Oracle database...
SQL*Plus: Release 12.2.0.1.0 Production on Mon Aug 29 06:16:40 2016
Copyright (c) 1982, 2016, Oracle. All rights reserved.
Last Successful login time: Fri Aug 26 2016 06:58:24 +01:00
Connected to:
Oracle Database 12c Enterprise Edition Release 12.2.0.1.0 - 64bit Production
Setup complete.
SQL queries complete.
OS commands complete.
Disconnected from Oracle Database 12c Enterprise Edition Release 12.2.0.1.0 - 64bit
Production
DBSAT Collector completed successfully.
Calling /u01/app/oracle/product/12.2.0/dbhome_2/bin/zip to encrypt dbsat_collect.json...
Enter password:
Verify password:
adding: dbsat_collect.json (deflated 87%)
zip completed successfully.

[oracle@host122 dbsat]$ ./dbsat report /tmp/dbsat_collect
...
Archive: /tmp/dbsat_collect.zip
[/tmp/dbsat_collect.zip] dbsat_collect.json password:
inflating: /tmp/dbsat_collect.json
DBSAT Reporter ran successfully.
Calling /usr/bin/zip to encrypt the generated reports...
Enter password:
Verify password:
adding: dbsat_collect.txt (deflated 78%)
adding: dbsat_collect.html (deflated 83%)
adding: dbsat_collect.xlsx (deflated 3%)
zip completed successfully.

DBSAT

not a typo

download from MOS

more on security

12.2

TDE online

SQL> select name from v$datafile;
NAME
--------------------------------------------------------
/u01/oradata/mydb/system01.dbf
/u01/oradata/mydb/sysaux01.dbf
/u01/oradata/mydb/undo01.dbf
/u01/oradata/mydb/users01.dbf
SQL> ALTER TABLESPACE users ENCRYPTION ONLINE USING 'AES192'
2 ENCRYPT FILE_NAME_CONVERT= ('users', 'users_enc');
SQL> select name from v$datafile;
NAME
----------------------------------------------------------
/u01/oradata/mydb/system01.dbf
/u01/oradata/mydb/sysaux01.dbf
/u01/oradata/mydb/undo01.dbf
/u01/oradata/mydb/users_enc01.dbf

18c+

data dictionary encryption

ACCOUNTING,KING,PRESIDENT,5000
ACCOUNTING,MILLER,CLERK,1300
203

<department name="ACCOUNTING">
<employees>
<employee>
<ename>KING</ename>
<job>PRESIDENT</job>
<sal>5000</sal>
</employee>
<employee>
<ename>MILLER</ename>
<job>CLERK</job>
<sal>1300</sal>
</employee>
</employees>
</department>
204

{ "NAME" :"ACCOUNTING"
, "EMPLOYEES" : [
{"ENAME" : "KING",
"JOB" : "PRESIDENT",
"SAL" : 5000
},
{"ENAME" : "MILLER",
"JOB" : "CLERK",
"SAL" : 1300
}]
}
205

12.1
206

alter table T
add constraint t_chk
check
(
my_doc is JSON
)
207

extraction
208

SQL> select json_value(my_doc,
2 '$.ACCOUNTING.EMPLOYEES[0].ENAME') as ename
3 from t;
ENAME
----------
KING
209

dot notation
210

SQL> select t.my_doc.ACCOUNTING.EMPLOYEES.ENAME emps,
2 t.my_doc.ACCOUNTING.EMPLOYEES.JOB jobs,
3 t.my_doc.ACCOUNTING.EMPLOYEES.SAL sals
4 from T t;
EMPS JOBS SALS
-------------------- ------------------- ---------------
[KING,MILLER] [PRESIDENT,CLERK] [5000,1300]
211

12.2
212

generation
213

{"newJSONfunctions": [
"json_array",
"json_object",
"json_arrayagg",
"json_objectagg"
] }

SQL> select
2 json_array(department_id, department_name) depts
3 from hr.departments
4 where department_id > 200;
DEPTS
--------------------------------------------------------
[210,"IT Support"]
[220,"NOC"]
[230,"IT Helpdesk"]
[240,"Government Sales"]
[250,"Retail Sales"]
[260,"Recruiting"]
[270,"Payroll"]
7 rows selected.

SQL> select
2 json_object(
3 'DeptID' is department_id,
4 'Name' is department_name) depts
5 from hr.departments
6 where department_id > 200;
DEPTS
------------------------------------------------
{"DeptID":210,"Name":"IT Support"}
{"DeptID":220,"Name":"NOC"}
{"DeptID":230,"Name":"IT Helpdesk"}
{"DeptID":240,"Name":"Government Sales"}
{"DeptID":250,"Name":"Retail Sales"}
{"DeptID":260,"Name":"Recruiting"}
{"DeptID":270,"Name":"Payroll"}
7 rows selected.

{
"department": "Accounting",
"employees": [
{
"name": "Shelley,Higgins",
"job": "Accounting Manager"
},
{
"name": "William,Gietz",
"job": "Public Accountant"
}
]
}

SQL> select json_object(
2 'department' value d.department_name,
3 'employees' value json_arrayagg(
4 json_object(
5 'name' value first_name||','||last_name,
6 'job' value job_title
7 )))
8 from hr.departments d, hr.employees e, hr.jobs j
9 where d.department_id = e.department_id
10 and e.job_id = j.job_id
11 and d.department_id = 110
12 group by d.department_name;

... and more JSON goodies
json_exists
GeoJSON
JSON Partitioning
In-Memory support
JSON Data Guide
Materialized Views
Search index

SQL> desc ORDERS
NAME TYPE
------------------ -----------
ORDER_DETAILS BLOB
{"date": "2016-05-03 10:40:36",
"loyaltyCardNo": 1230,
"location": {
"city": "Dallas",
"state": "TX"},
"salesAmount": 7.55,
"order": [ {
"item": "Espresso", ... }
}

SQL> SELECT JSON_DATAGUIDE(o.order_details) FROM orders o;
JSON_DATAGUIDE(O.ORDER_DETAILS)
----------------------------------------------------------------------
[ {"o:path": "$.date", "type": "string", "o:length": 32 },
{"o:path": "$.order", "type": "array", "o:length": 256 },
{"o:path": "$.location", "type": "object", "o:length": 32},
{"o:path": "$.location.city", "type": "string", "o:length": 8},
...
...
{ "o:path": "$.salesAmount", "type": "number", "o:length": 4 },
{ "o:path": "$.loyaltyCardNo","type": "number", "o:length": 8}]

18c+

better data handling

json_array
json_object
json_arrayagg
json_objectagg
VARCHAR2 VARCHAR2

json_array
json_object
json_arrayagg
json_objectagg
BINARY_DOUBLE
BINARY_FLOAT
CLOB
BLOB
NVARCHAR2
RAW
TIMESTAMP WITH TIME ZONE
TIMESTAMP WITH LOCAL TIME ZONE
INTERVAL YEAR TO MONTH
INTERVAL DAY TO SECOND
BLOB
CLOB

TREAT clause

SQL> with emps as
2 (
3 select '{"empno":1234, "ename":"Connor"}' j
4 from dual
5 )
6 select e.j.empno from emps e;
select e.j.empno from emps e
*
ERROR at line 6:
ORA-00904: "E"."J"."EMPNO": invalid identifier

SQL> with emps as
2 (
3 select '{"empno":1234, "ename":"Connor"}' j
4 from dual
5 ),
6 json_emps as
7 (
8 select treat(j as json) js
9 from emps
10 )
11 select je.js.empno
12 from json_emps je;
EMPNO
-----------------------------------------------------
1234

JSON_EQUAL

{ "NAME" :"ACCOUNTING",
"EMPLOYEES" : [
{"ENAME" : "KING",
"JOB" : "PRESIDENT",
"SAL" : 5000
},
"JOB" : "CLERK",
"SAL" : 1300
}
]
}
{
"EMPLOYEES" : [
{"ENAME" : "KING",
"SAL" : 5000,
"JOB" : "PRESIDENT"
},
"JOB" : "CLERK",
"SAL" : 1300
}
], "NAME" :"ACCOUNTING"
}

19c

partial/fragment update

let's talk about ...
234

polyglot persistence
235

2016 Perth branch meeting !
237

"I have to learn Hadoop
....and Spark
....and Hive
....and ?"

Big Data SQL

19c

hybrid partitioned table

Q4_2018Q3_2018Q2_2018Q1_2018Q4_2017Q3_2017Q2_2017Q1_2017Q4_2016
ORDERS
OBJECT STORAGE
TABLE PARTITIONED BY QUARTER
SQL HOT DATACOLD DATA
UPDATES
* manual transfer initially

global temporary tablesprivate

SQL server etc

read locking

SELECT empno, ename, job
INTO #HighPaidJobs
FROM emp
WHERE sal > 3000

migration to Oracle difficult

SQL> create private temporary table ORA$PTT_MY_TT
2 ( empno int , ename varchar2(20)) ;
Table created.
SQL> insert into ORA$PTT_MY_TT
2 select empno, ename
3 from scott.emp
4 where sal > 3000;
1 row created.
SQL> select * from ORA$PTT_MY_TT;
EMPNO ENAME
---------- --------------------
7839 KING

"um...looks the same as before"

SQL> commit;
Commit complete.
select * from ORA$PTT_MY_TT
*
ERROR at line 1:
ORA-00942: table or view does not exist

it's really temporary

2 ( empno int , ename varchar2(20)) ;
Table created.
SQL> select *
2 from user_tables
3 where table_name = 'ORA$PTT_MY_TT' ;
no rows selected
SQL> select *
2 from all_objects
3 where object_name = 'ORA$PTT_MY_TT' ;
no rows selected

2 ( empno , ename )
3 on commit preserve definition
4 as select 123, 'Larry' from dual;
EMPNO ENAME
---------- -----
123 Larry
SQL> commit;
EMPNO ENAME
---------- -----
123 Larry

it's really private

2 ( empno int ,
3 ename varchar2(20)) ;
Table created.
2 ( deptno int ,
3 dname varchar2(20),
4 bonus int,
5 logo blob) ;
Table created.

it's all in the name !

SQL> create private temporary table MY_TT ( x int ) ;
create private temporary table MY_TT ( x int )
*
ERROR at line 1:
ORA-00903: invalid table name
SQL> show parameter private
NAME TYPE VALUE
------------------------------- ----------- -----------
private_temp_table_prefix string ORA$PTT_

this is the big one
261

18c XE
262

100% free

We grant you a nonexclusive, nontransferable limited license to use the programs for:
(a) purposes of developing, prototyping and running your applications for your own
internal data processing operations;
(b) you may also distribute the programs with your applications;
(c) you may use the programs to provide third party demonstrations and training; and
d) you may copy and distribute the programs to your licensees provided that each such
licensee agrees to the terms of this Agreement
https://www.oracle.com/technetwork/licenses/db18c-express-license-5137264.html

12 GB of user data
2 GB of database RAM
2 CPU threads
3 Pluggable Databases

"Is it feature hobbled?"

Oracle Multitenant
SQLJ
Online index rebuild
Online table reorg
Online table redefinition
Trial recovery
Fast start recovery
Flashback table
Flashback query
Flashback database
Advanced Queueing
Network Compression
Client side result cache
Server side result cache
Adaptive plans
In-memory column store
In-memory aggregation
Attribute Clustering
Column encryption
Tablespace encryption
Advanced Security
Database Vault
Label Security
AD users
Privilege Analysis
Real Application Security
Data Redaction
Virtual Private Database
Spatial
Graph
Partitioning
Advanced Analytics
Advanced Compression
Advanced Index Compression
Transportable Tablespace
Query Rewrite

EE plus most extra cost options

wrap up

there's a lot in 12.2/18/19

new feature model

"dribs and drabs" :-)

lots not covered today

plenty to excite
275

Stay in touch!
youtube bit.ly/youtube-connor
blog bit.ly/blog-connor
twitter bit.ly/twitter-connor

Perth APAC Groundbreakers tour - 18c features

Recommandé

Recommandé

Contenu connexe

Tendances

Tendances (20)

Similaire à Perth APAC Groundbreakers tour - 18c features

Similaire à Perth APAC Groundbreakers tour - 18c features (20)

Plus de Connor McDonald

Plus de Connor McDonald (20)

Dernier

Dernier (20)

Perth APAC Groundbreakers tour - 18c features

Notes de l'éditeur