arc The Automotive Adaptive Front Lighting Market is LED by Europe, as per Maximize Market Research. By www.emailwire.com Published On :: Wed, 30 Oct 2024 00:00:00 -0700 (EMAILWIRE.COM, October 30, 2024 ) Growing vehicle manufacturing is driving the need for enhanced lighting systems worldwide. Increased visibility during nighttime decreases accidents, prompting more stringent regulations and greater consumer demand for these safety systems. Adaptive headlights are... Full Article
arc The Rainwater Harvesting Market is dominated by Roof-based harvesting, as per Maximize Market Research. By www.emailwire.com Published On :: Wed, 30 Oct 2024 00:00:00 -0700 (EMAILWIRE.COM, October 30, 2024 ) Due to growing water scarcity and environmental worries, the rainwater harvesting market offers a substantial potential for expansion. The increasing importance of alternative water sources is expected to lead to a rise in the use of rainwater harvesting systems... Full Article
arc Butadiene Market was is expected to grow $50.93 Bn by 2030, as per Maximize Market Research. By www.emailwire.com Published On :: Thu, 31 Oct 2024 00:00:00 -0700 (EMAILWIRE.COM, October 31, 2024 ) The Butadiene market is expected to reach US$ 50.93 Bn. in 2030, with a CAGR of 4.4% for the period 2024-2030, because of growing demand in the tire industry. The butadiene market, a key component in synthetic rubber and automotive parts, is navigating a complex... Full Article
arc Automotive Adaptive Front Lighting Market was is expected to grow $6.55 Bn by 2030, as per Maximize Market Research. By www.emailwire.com Published On :: Thu, 31 Oct 2024 00:00:00 -0700 (EMAILWIRE.COM, October 31, 2024 ) Automotive Adaptive Front Lighting Market is expected to grow at a CAGR of 27.8% throughout the forecast period, to reach US$ 6.55 Bn. by 2030 The global automotive adaptive front lighting market is on the rise, driven by increasing safety concerns and consumer... Full Article
arc Digital Instrument Cluster Market Growth Accelerates with Rising Demand in Automotive Sector, as per Maximize Market Research. By www.emailwire.com Published On :: Fri, 01 Nov 2024 00:00:00 -0700 (EMAILWIRE.COM, November 01, 2024 ) The global Digital Instrument Cluster market is witnessing rapid growth, fueled by increasing demand for advanced automotive displays and enhanced in-car experiences. Driven by advancements in digital interfaces, these clusters provide customizable, high-resolution... Full Article
arc The Cloud High Performance Computing Market Set for Rapid Growth as Demand Surges, as per Maximize Market Research. By www.emailwire.com Published On :: Fri, 01 Nov 2024 00:00:00 -0700 (EMAILWIRE.COM, November 01, 2024 ) The global Cloud High Performance Computing (HPC) market is poised for significant expansion, driven by growing demands in industries such as healthcare, finance, and automotive. Cloud HPC enables businesses to perform complex computations and simulations faster... Full Article
arc Europe Wireless Headphones Market Expands as Demand for High-Quality Audio and Mobility Grows, as per Maximize Market Research. By www.emailwire.com Published On :: Fri, 01 Nov 2024 00:00:00 -0700 (EMAILWIRE.COM, November 01, 2024 ) The Europe Wireless Headphones market is experiencing substantial growth, driven by rising consumer preference for high-quality audio and seamless mobility. With advancements in noise-canceling technology, battery life, and Bluetooth connectivity, wireless headphones... Full Article
arc Artificial Intelligence (AI) Chipset Market is expected to grow at 40% CAGR from 2024 to 2030, as per Maximize Market Research By www.emailwire.com Published On :: Fri, 01 Nov 2024 00:00:00 -0700 (EMAILWIRE.COM, November 01, 2024 ) Artificial Intelligence Chipset Market size was valued US$ 20.76 Bn in 2023 and the total revenue is expected to grow at 40% from 2024 to 2030, reaching US$ 218.85 Bn. by 2030. The AI chipset market is experiencing rapid growth, driven by increasing adoption... Full Article
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arc Aliphatic Amines Market Expands Due to Demand in Agriculture and Chemical Manufacturing, as per Maximize Market Research By www.emailwire.com Published On :: Sun, 03 Nov 2024 00:00:00 -0700 (EMAILWIRE.COM, November 03, 2024 ) Aliphatic Amines Market are substances created through displacement reaction within an ammonia molecule. Monovalent hydrocarbon radicals replaced the hydrogen atoms in ammonia in Aliphatic Amines. The analysis in the report examines how the COVID-19 pandemic... Full Article
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arc Aluminum Flat Rolled Products Market Sees Strong Growth with Demand from Automotive and Construction Sectors, as per Maximize Market Research By www.emailwire.com Published On :: Mon, 04 Nov 2024 00:00:00 -0800 (EMAILWIRE.COM, November 04, 2024 ) The Aluminum Flat Rolled Products Market is set for expansion as demand rises in automotive, construction, and packaging industries. Aluminums lightweight and corrosion-resistant properties make it ideal for use in energy-efficient vehicles and sustainable buildings.... Full Article
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arc Apron Bus Market Grows with Expanding Air Travel and Airport Operations, as per Maximize Market Research By www.emailwire.com Published On :: Mon, 04 Nov 2024 00:00:00 -0800 (EMAILWIRE.COM, November 04, 2024 ) The Global Apron Bus Market is expanding, supported by the growth in air travel and the need for efficient airport ground operations. Apron buses transport passengers between terminals and aircraft, ensuring smooth and timely boarding. Key manufacturers are innovating... Full Article
arc AI in Fashion Market Grows as Industry Embraces Digital Transformation, as per Maximize Market Research By www.emailwire.com Published On :: Tue, 05 Nov 2024 00:00:00 -0800 (EMAILWIRE.COM, November 05, 2024 ) The Global AI in Fashion Market is expanding rapidly, with brands leveraging AI to enhance design, personalization, and inventory management. From predictive analytics to virtual try-ons, AI is revolutionizing consumer engagement and operational efficiency. Fashion... Full Article
arc Aerostat Systems Market Gains Traction in Defense and Surveillance Applications, as per Maximize Market Research By www.emailwire.com Published On :: Tue, 05 Nov 2024 00:00:00 -0800 (EMAILWIRE.COM, November 05, 2024 ) An Aerostat Systems Market is an aircraft lighter than air that achieves lift with the help of a buoyant gas. Aerostat systems consist of unpowered balloons as well as powered airships. A balloon can fly freely or be anchored. Request For Free Sample Report... Full Article
arc Exoskeleton Market Poised for Growth with Demand in Healthcare and Industrial Sectors, as per Maximize Market Research By www.emailwire.com Published On :: Tue, 05 Nov 2024 00:00:00 -0800 (EMAILWIRE.COM, November 05, 2024 ) The Exoskeleton Market is projected to grow rapidly, driven by applications in healthcare rehabilitation and industrial productivity. Exoskeletons enhance mobility for those with disabilities and improve worker efficiency and safety in industries such as manufacturing... Full Article
arc Market Research Insight: India's Drone Market on a High-Flying Growth Trajectory By www.emailwire.com Published On :: Tue, 12 Nov 2024 00:00:00 -0800 (EMAILWIRE.COM, November 12, 2024 ) The India Drone Market is witnessing a remarkable surge, with a projected growth from USD 654 million in 2024 to USD 1,437 million by 2029, driven by an impressive CAGR of 17.0%. This growth trajectory indicates a transformative shift in the adoption and application... Full Article
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arc Google Enters Another Market (Custom Search) By tedshelton.blogspot.com Published On :: 2006-10-24T05:29:00Z Everyone on the Internet fears the day that Google will enter their market. Today the fear was tangible for Rollyo and Swicki. The Financial Times reported that Google will launch tomorrow (Tuesday) "...a customisable search engine that users can carry on their own blogs and other websites..." and compares the new service to Rollyo. Matthew Ingram carries the photo of a shark on his post about this development. Ingram points out that when Google entered the calendar market, competitor Kiko gave up and sold themselves. He asks whether or not this was the right decision -- pointing to Paul Graham's post at the time "Google Does Not Render Resistance Futile." I find myself agreeing with Paul and Rex Hammock puts his finger on it when he writes: There’s a social networking aspect of Rollyo that probably won’t be a part of the Google product, however the Google product will likely offer publishers, including bloggers, an instant way to monetize narrow search in the Adsense program they’re already participating in.For all of the things that Google has done right in technology, they have done very little well in the category of social. It isn't too late for them to learn but if history is any guide, they will miss the importance of the social network in search as well.And frankly having a strong competitor forces you to do the two things which you most need to do in any case when you are a small business -- innovate constantly and be 500% better than your larger competition. Then Google can educate the market about why the market needs your product and then you can deliver on the market's expectations. That is what YouTube did. Full Article
arc La Chine adopte des politiques fiscales pour soutenir le march� de l'immobilier By chine.in Published On :: 2024-11-13T19:48:44+01:00 La Chine a promulgu� mercredi des politiques fiscales pour soutenir le d�veloppement stable et sain du march� de l'immobilier. Le minist�re des Finances a d�clar� que le pays augmenterait les incitations en termes de taxe sur les actes pour... Full Article immobilier
arc 12C: IN DATABASE ARCHIVING By www.orafaq.com Published On :: Sun, 28 Jul 2013 08:42:59 +0000 articles: Technical ArticlesIn this post, I will demonstrate a new feature introduced in 12c : In database archiving. It enables you to archive rows within a table by marking them as invisible. This is accomplshed by means of a hidden column ORA_ARCHIVE_STATE. These invisible rows are not visible to the queries but if needed, can be viewed , by setting a session parameter ROW ARCHIVAL VISIBILITY. Overview: -- Create test user uilm, tablespace ilmtbs -- Connect as user uilm -- create and populate test table (5 rows) ilmtab with row archival clause -- Note that the table has an additional column ORA_ARCHIVE_STATE automatically created and has the default value of 0 (indicates that row is active) -- Note that this column is not visible when we describe the table or simply issue select * from ... -- We need to access data dictionary to view the column -- Make two rows in the table inactive by setting ORA_ARCHIVE_STATE column to a non zero value. -- Check that inactive rows are not visible to query -- Set the parameter ROW ARCHIVAL VISIBILITY = all to see inactive rows also -- Set the parameter ROW ARCHIVAL VISIBILITY = active to hide inactive rows -- Issue an insert into ... select * and check that only 3 visible rows are inserted -- Set the parameter ROW ARCHIVAL VISIBILITY = all to see inactive rows also -- Issue an insert into ... select * and check that all the rows are inserted but ORA_ARCHIVE_STATE is not propagated in inserted rows -- Disable row archiving in the table and check that column ORA_ARCHIVE_STATE is automatically dropped -- drop tablespace ilmtbs and user uilm Implementation : -- Create test user, tablespace and test table SQL> conn sys/oracle@em12c:1523/pdb1 as sysdba sho con_name CON_NAME ------------------------------ PDB1 SQL> set sqlprompt PDB1> PDB1>create tablespace ilmtbs datafile '/u02/app/oracle/oradata/cdb1/pdb1/ilmtbs01.dbf' size 1m; grant connect, resource, dba to uilm identified by oracle; alter user uilm default tablespace ilmtbs; conn uilm/oracle@em12c:1523/pdb1 sho con_name CON_NAME ------------------------------ PDB1-- create table with "row archival clause" PDB1>drop table ilmtab purge; create table ilmtab (id number, txt char(15)) row archival; insert into ilmtab values (1, 'one'); insert into ilmtab values (2, 'two'); insert into ilmtab values (3, 'three'); insert into ilmtab values (4, 'four'); insert into ilmtab values (5, 'five'); commit;-- Note that the table has an additional column ORA_ARCHIVE_STATE automatically created and has the default value of 0 (indicates that row is active) PDB1>col ora_archive_state for a20 select id, txt, ora_archive_state from ilmtab; ID TXT ORA_ARCHIVE_STATE ---------- --------------- -------------------- 1 one 0 2 two 0 3 three 0 4 four 0 5 five 0-- Note that this column is not visible when we describe the table or simply issue select * from ... PDB1>desc ilmtab Name Null? Type ----------------------------------------- -------- ---------------------------- ID NUMBER TXT CHAR(15) PDB1>select * from ilmtab; ID TXT ---------- --------------- 1 one 2 two 3 three 4 four 5 five -- Since the column is invisible, let me try and make it visible-- Note that Since the column is maintained by oracle itself, user can't modify its attributes PDB1>alter table ilmtab modify (ora_archive_state visible); alter table ilmtab modify (ora_archive_state visible) *ERROR at line 1:ORA-38398: DDL not allowed on the system ILM column -- We need to access data dictionary to view the column-- Note that this column is shown as hidden and has not been generated by user PDB1>col hidden for a7 col USER_GENERATED for 20 col USER_GENERATED for a20 select TABLE_NAME, COLUMN_NAME, HIDDEN_COLUMN, USER_GENERATED from user_tab_cols where table_name='ILMTAB'; TABLE_NAME COLUMN_NAME HID USER_GENERATED ----------- -------------------- --- -------------------- ILMTAB ORA_ARCHIVE_STATE YES NO ILMTAB ID NO YES ILMTAB TXT NO YES-- We can make selected rows in the table inactive by setting ORA_ARCHIVE_STATE column to a non zero value. This can be accomplished using update table... set ORA_ACRHIVE_STATE = . <non-zero value> . dbms_ilm.archivestatename(1) -- Let's update row with id =1 with ORA_ARCHIVE_STATE=2 and update row with id =2 with dbms_ilm.archivestatename(2) PDB1>update ilmtab set ora_archive_state=2 where id=1; update ilmtab set ora_archive_state= dbms_ilm.archivestatename(2) where id=2;-- Let's check whether updates have been successful and hidden rows are not visible PDB1>select id, txt, ORA_ARCHIVE_STATE from ilmtab; ID TXT ORA_ARCHIVE_STATE ---------- --------------- -------------------- 3 three 0 4 four 0 5 five 0 -- The updated rows are not visible!! -- Quite logical since we have made the rows active and by default only active rows are visible -- To see inactive rows also, we need to set the parameter ROW ARCHIVAL VISIBILITY = all at session level -- Note that the column ORA_ARCHIVE_STATE has been set to 1 for id =2 although we had set it to 2 using dbms_ilm.archivestatename(2) PDB1>alter session set ROW ARCHIVAL VISIBILITY = all; select id, txt, ORA_ARCHIVE_STATE from ilmtab; ID TXT ORA_ARCHIVE_STATE ---------- --------------- -------------------- 1 one 2 2 two 1 3 three 0 4 four 0 5 five 0-- Note that the column ORA_ARCHIVE_STATE has been set to 1 for id =2 although we had set it to 2 using dbms_ilm.archivestatename(2) -- Let's find out why-- Note that The function dbms_ilm.archivestatename(n) returns only two values 0 for n=0 and 1 for n <> 0 PDB1>col state0 for a8 col state1 for a8 col state2 for a8 col state3 for a8 select dbms_ilm.archivestatename(0) state0 ,dbms_ilm.archivestatename(1) state1, dbms_ilm.archivestatename(2) state2,dbms_ilm.archivestatename(3) state3 from dual; STATE0 STATE1 STATE2 STATE3 -------- -------- -------- -------- 0 1 1 1-- In order to make the inactive rows (id=1,2) hidden again, we need to set the parameter ROW ARCHIVAL VISIBILITY = Active PDB1>alter session set row archival visibility = active; select id, txt, ORA_ARCHIVE_STATE from ilmtab; ID TXT ORA_ARCHIVE_STATE ---------- --------------- -------------------- 3 three 0 4 four 0 5 five 0-- Let's issue an insert into ... select * -- Note that only 3 new rows are visible PDB1>insert into ilmtab select * from ilmtab; select id, txt, ora_archive_state from ilmtab; ID TXT ORA_ARCHIVE_STATE ---------- --------------- -------------------- 3 three 0 4 four 0 5 five 0 3 three 0 4 four 0 5 five 0 6 rows selected. -- I want to check if hidden rows were also inserted -- Let's check by making hidden rows visible again-- Note that only visible rows(id=3,4,5) were inserted PDB1>alter session set row archival visibility=all; select id, txt, ora_archive_state from ilmtab; ID TXT ORA_ARCHIVE_STATE ---------- --------------- -------------------- 1 one 2 2 two 1 3 three 0 4 four 0 5 five 0 3 three 0 4 four 0 5 five 0 8 rows selected.-- Let's set row archival visibility = all and then again insert rows from ilmtab-- Note that all the 8 rows are inserted but ORA_ARCHIVE_STATE ha not been copied ORA_ARCHIVE_STATE <> 0 in only 2 records (id = 1,2) even now. PDB1>alter session set row archival visibility=all; insert into ilmtab select * from ilmtab; select id, txt, ora_archive_state from ilmtab order by id; ID TXT ORA_ARCHIVE_STATE ---------- --------------- -------------------- 1 one 0 1 one 2 2 two 0 2 two 1 3 three 0 3 three 0 3 three 0 3 three 0 4 four 0 4 four 0 4 four 0 4 four 0 5 five 0 5 five 0 5 five 0 5 five 0 16 rows selected.-- Disable row level archiving for the table -- Note that as soon as row archiving is disabled, pseudo column ora_archive_state is dropped automatically PDB1>alter table ilmtab no row archival; select id, txt, ORA_ARCHIVE_STATE from ilmtab; ERROR at line 1:ORA-00904: "ORA_ARCHIVE_STATE": invalid identifier PDB1>col hidden for a7 col USER_GENERATED for 20 col USER_GENERATED for a20 select TABLE_NAME, COLUMN_NAME, HIDDEN_COLUMN, USER_GENERATED from user_tab_cols where table_name='ILMTAB'; TABLE_NAME COLUMN_NAME HID USER_GENERATED ----------- -------------------- --- -------------------- ILMTAB ID NO YES ILMTAB TXT NO YESNote : Had we created this table using sys, we could not have disabled row archiving . -- cleanup -- PDB1>conn sys/oracle@em12c:1523/pdb1 as sysdba drop tablespace ilmtbs including contents and datafiles; drop user uilm cascade;References: http://docs.oracle.com/cd/E16655_01/server.121/e17613/part_lifecycle.htm#VLDBG14154 ---------------------------------------------------------------------------------------------------- Oracle 12c Index ---------------------------------------------------------------------------------------------- Full Article
arc Recursive WITH, part II: Hierarchical queries By www.orafaq.com Published On :: Fri, 03 Jun 2016 09:38:25 +0000 articles: SQL & PL/SQLIn my last post, I looked at using recursive WITH to implement simple recursive algorithms in SQL. One very common use of recursion is to traverse hierarchical data. I recently wrote a series of posts on hierarchical data, using Oracle’s CONNECT BY syntax and a fun example. In this post, I’ll be revisiting the same data using recursive WITH. There are dozens of examples of hierarchical data, from the EMP table to the Windows Registry to binary trees, but I went with something more fun: the skeleton from the old song “Dem Dry Bones”. Quote:Toe bone connected to the foot bone Foot bone connected to the heel bone Heel bone connected to the ankle bone Ankle bone connected to the shin bone Shin bone connected to the knee bone Knee bone connected to the thigh bone Thigh bone connected to the hip bone Hip bone connected to the back bone Back bone connected to the shoulder bone Shoulder bone connected to the neck bone Neck bone connected to the head bone Since every bone has only one ancestor, and there is a root bone with no ancestor, this is hierarchical data and we can stick it in a table and query it. SELECT * FROM skeleton; BONE CONNECTED_TO_THE ---------------------------------------- ---------------------------------------- shoulder neck back shoulder hip back thigh hip knee thigh leg knee foot heel head neck head toe foot arm shoulder wrist arm ankle leg heel ankle finger wrist a rib back b rib back c rib back You can see that I added some ribs and an arm to make the skeleton more complete! Using Oracle’s CONNECT BY syntax: SQL> col bone FOR a10 SQL> col connected_to_the FOR a9 SQL> col level FOR 99 SQL> col bone_tree FOR a27 SQL> col path FOR a65 SELECT bone, connected_to_the, level, lpad(' ',2*level, ' ') || bone AS bone_tree , ltrim(sys_connect_by_path(bone,'>'),'>') AS path FROM skeleton START WITH connected_to_the IS NULL CONNECT BY prior bone=connected_to_the ORDER siblings BY 1 BONE CONNECTED LEVEL BONE_TREE PATH ---------- --------- ----- --------------------------- ----------------------------------------------------------------- head 1 head head neck head 2 neck head>neck shoulder neck 3 shoulder head>neck>shoulder arm shoulder 4 arm head>neck>shoulder>arm wrist arm 5 wrist head>neck>shoulder>arm>wrist finger wrist 6 finger head>neck>shoulder>arm>wrist>finger back shoulder 4 back head>neck>shoulder>back a rib back 5 a rib head>neck>shoulder>back>a rib b rib back 5 b rib head>neck>shoulder>back>b rib c rib back 5 c rib head>neck>shoulder>back>c rib hip back 5 hip head>neck>shoulder>back>hip thigh hip 6 thigh head>neck>shoulder>back>hip>thigh knee thigh 7 knee head>neck>shoulder>back>hip>thigh>knee leg knee 8 leg head>neck>shoulder>back>hip>thigh>knee>leg ankle leg 9 ankle head>neck>shoulder>back>hip>thigh>knee>leg>ankle heel ankle 10 heel head>neck>shoulder>back>hip>thigh>knee>leg>ankle>heel foot heel 11 foot head>neck>shoulder>back>hip>thigh>knee>leg>ankle>heel>foot toe foot 12 toe head>neck>shoulder>back>hip>thigh>knee>leg>ankle>heel>foot>toe The above CONNECT BY query uses the LEVEL pseudocolumn and the SYS_CONNECT_BY_PATH function. With recursive WITH, there’s no need for these built-ins because these values fall naturally out of the recursion. Let’s start with the basic hierarchical query rewritten in recursive WITH. The hierarchical relationship in our table is: Parent(row.bone) = row.connected_to_the WITH skellarchy (bone, parent) AS ( SELECT bone, connected_to_the FROM skeleton WHERE bone = 'head' -- Start with the root UNION ALL SELECT s.bone, s.connected_to_the FROM skeleton s, skellarchy r WHERE r.bone = s.connected_to_the -- Parent(row.bone) = row.connected_to_the ) SELECT * FROM skellarchy; BONE PARENT ---------- ---------------------------------------- head neck head shoulder neck back shoulder arm shoulder hip back wrist arm a rib back b rib back c rib back thigh hip finger wrist knee thigh leg knee ankle leg heel ankle foot heel toe foot Because we built up the SKELLARCHY table recursively, it’s easy to make an equivalent to the LEVEL pseudocolumn; it falls right out of the recursion: WITH skellarchy (bone, parent, the_level) AS ( SELECT bone, connected_to_the, 0 FROM skeleton WHERE bone = 'head' UNION ALL SELECT s.bone, s.connected_to_the , r.the_level + 1 FROM skeleton s, skellarchy r WHERE r.bone = s.connected_to_the ) SELECT * FROM skellarchy; BONE PARENT THE_LEVEL ---------- ---------- ---------- head 0 neck head 1 shoulder neck 2 back shoulder 3 arm shoulder 3 hip back 4 wrist arm 4 a rib back 4 b rib back 4 c rib back 4 thigh hip 5 finger wrist 5 knee thigh 6 leg knee 7 ankle leg 8 heel ankle 9 foot heel 10 toe foot 11 and it’s also easy to build up a path from root to the current node like the “SYS_CONNECT_BY_PATH” function does for CONNECT BY queries: WITH skellarchy (bone, parent, the_level, the_path) AS ( SELECT bone, connected_to_the, 0, CAST(bone AS varchar2(4000)) FROM skeleton WHERE bone = 'head' UNION ALL SELECT s.bone, s.connected_to_the , r.the_level + 1, r.the_path || '->' || s.bone FROM skeleton s, skellarchy r WHERE r.bone = s.connected_to_the ) SELECT * FROM skellarchy; BONE PARENT THE_LEVEL THE_PATH ---------- ---------- --------- -------------------------------------------------------------------------------- head 0 head neck head 1 head->neck shoulder neck 2 head->neck->shoulder back shoulder 3 head->neck->shoulder->back arm shoulder 3 head->neck->shoulder->arm hip back 4 head->neck->shoulder->back->hip wrist arm 4 head->neck->shoulder->arm->wrist a rib back 4 head->neck->shoulder->back->a rib b rib back 4 head->neck->shoulder->back->b rib c rib back 4 head->neck->shoulder->back->c rib thigh hip 5 head->neck->shoulder->back->hip->thigh finger wrist 5 head->neck->shoulder->arm->wrist->finger knee thigh 6 head->neck->shoulder->back->hip->thigh->knee leg knee 7 head->neck->shoulder->back->hip->thigh->knee->leg ankle leg 8 head->neck->shoulder->back->hip->thigh->knee->leg->ankle heel ankle 9 head->neck->shoulder->back->hip->thigh->knee->leg->ankle->heel foot heel 10 head->neck->shoulder->back->hip->thigh->knee->leg->ankle->heel->foot toe foot 11 head->neck->shoulder->back->hip->thigh->knee->leg->ankle->heel->foot->toe and we can use our generated the_level column to make a nice display just as we used the level pseudocolumn with CONNECT BY: WITH skellarchy (bone, parent, the_level) AS ( SELECT bone, connected_to_the, 0 FROM skeleton WHERE bone = 'head' UNION ALL SELECT s.bone, s.connected_to_the , r.the_level + 1 FROM skeleton s, skellarchy r WHERE r.bone = s.connected_to_the ) SELECT lpad(' ',2*the_level, ' ') || bone AS bone_tree FROM skellarchy; BONE_TREE --------------------------- head neck shoulder back arm hip wrist a rib b rib c rib thigh finger knee leg ankle heel foot toe Now, the bones are coming out in a bit of a funny order for a skeleton. Instead of this: shoulder back arm hip wrist a rib b rib c rib thigh finger I want to see this: shoulder arm wrist finger back a rib b rib c rib hip thigh The rows are coming out in BREADTH FIRST ordering – meaning all siblings of ‘shoulder’ are printed before any children of ‘shoulder’. But I want to see them in DEPTH FIRST: going from shoulder to finger before we start on the backbone. WITH skellarchy (bone, parent, the_level) AS ( SELECT bone, connected_to_the, 0 FROM skeleton WHERE bone = 'head' UNION ALL SELECT s.bone, s.connected_to_the , r.the_level + 1 FROM skeleton s, skellarchy r WHERE r.bone = s.connected_to_the ) SEARCH DEPTH FIRST BY bone SET bone_order SELECT lpad(' ',2*the_level, ' ') || bone AS bone_tree FROM skellarchy ORDER BY bone_order; BONE_TREE --------------------------- head neck shoulder arm wrist finger back a rib b rib c rib hip thigh knee leg ankle heel foot toe And now the result looks more like a proper skeleton. Now on to cycles. A cycle is a loop in the hierarchical data: a row is its own ancestor. To put a cycle in the example data, I made the skeleton bend over and connect the head to the toe: UPDATE skeleton SET connected_to_the='toe' WHERE bone='head'; And now if we try to run the query: ERROR at line 2: ORA-32044: cycle detected while executing recursive WITH query With the CONNECT BY syntax, we can use CONNECT BY NOCYCLE to run a query even when cycles exist, and the pseudocolumn CONNECT_BY_IS_CYCLE to help detect cycles. For recursive WITH, Oracle provides a CYCLE clause, which is a bit more powerful as it allows us to name the column which is cycling. WITH skellarchy (bone, parent, the_level) AS ( SELECT bone, connected_to_the, 0 FROM skeleton WHERE bone = 'head' UNION ALL SELECT s.bone, s.connected_to_the , r.the_level + 1 FROM skeleton s, skellarchy r WHERE r.bone = s.connected_to_the ) SEARCH DEPTH FIRST BY bone SET bone_order CYCLE bone SET is_a_cycle TO 'Y' DEFAULT 'N' SELECT lpad(' ',2*the_level, ' ') || bone AS bone_tree, is_a_cycle FROM skellarchy --where is_a_cycle='N' ORDER BY bone_order; BONE_TREE I ------------------------------------------------------------ - head N neck N shoulder N arm N wrist N finger N back N a rib N b rib N c rib N hip N thigh N knee N leg N ankle N heel N foot N toe N head Y The query runs until the first cycle is detected, then stops. The CONNECT BY syntax does provide a nice pseudocolumn, CONNECT_BY_ISLEAF, which is 1 when a row has no further children, 0 otherwise. In my next post, I’ll look at emulating this pseudocolumn with recursive WITH. Republished with permission. Original URL: http://rdbms-insight.com/wp/?p=103 Full Article
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