Please take a look at https://phoenix.apache.org/views.html All views are 'virtual' tables, so they don't have a dedicated physical table and operates on top of the table that is specified in the view DDL.
Thanks, Sergey On Sat, Nov 25, 2017 at 6:25 AM, Eisenhut, Roman <[email protected]> wrote: > Dear Phoenix-Team, > > > > I did some test on bulk-loading data with the psql.py script in > $PHOENIX_HOME/bin and the tpc-h data on my cluster with 1 master and 3 RS. > I’ve found that it makes quite a difference whether you: > > 1. Create a table > 2. Bulk load data into that table > > Or > > 1. Create a table > 2. Create a view > 3. Bulk load data in the view > > > > I was wondering where the overhead is coming from? (you can find my > numbers below) > > > > Additionally, I created a view over a table which was already filled and > phoenix returned “No rows affected”. At the same time I can’t find a table > in HBase that reflects the view, which makes me wonder whether views are > actually materialized somewhere. As I’m quite interested in the view > functionality of Phoenix, I was wondering whether someone can explain what > is happening when a view is created? > > > > Best regards, > > Roman > > > > > > *psql.py -t X -d '|' X.csv, where X = table name* > > *ID* > > *TABLE* > > *region* > > *nation* > > *supplier* > > *customer* > > *part* > > *partsupp* > > *orders* > > *lineitem* > > *5* > > *25.00* > > *10,000* > > *150,000* > > *200,000* > > *800,000* > > *1,500,000* > > *6,001,215* > > *1* > > 0.068 > > 0.11 > > 2.959 > > 18.789 > > 27.881 > > 107.03 > > 164.853 > > 1007.315 > > *2* > > 0.124 > > 0.093 > > 2.993 > > 19.62 > > 26.954 > > 80.671 > > 169.038 > > 1039.294 > > *3* > > 0.07 > > 0.092 > > 2.795 > > 20.745 > > 29.036 > > 76.855 > > 177.765 > > 1042.642 > > *4* > > 0.132 > > 0.101 > > 2.89 > > 20.527 > > 28.121 > > 78.956 > > 180.145 > > 1019.047 > > *5* > > 0.072 > > 0.116 > > 3.334 > > 27.494 > > 28.891 > > 75.455 > > 166.668 > > 1011.299 > > *MIN* > > 0.068 > > 0.092 > > 2.795 > > 18.789 > > 26.954 > > 75.455 > > 164.853 > > 1007.315 > > *MAX* > > 0.132 > > 0.116 > > 3.334 > > 27.494 > > 29.036 > > 107.03 > > 180.145 > > 1042.642 > > *AVG* > > 0.0932 > > 0.1024 > > 2.9942 > > 21.435 > > 28.1766 > > 83.7934 > > 171.6938 > > 1023.919 > > > > *psql.py -t X_VIEW -d '|' X.csv, where X = table name* > > *ID* > > *VIEW* > > *region* > > *nation* > > *supplier* > > *customer* > > *part* > > *partsupp* > > *orders* > > *lineitem* > > *5* > > *25.00* > > *10,000* > > *150,000* > > *200,000* > > *800,000* > > *1,500,000* > > *6,001,215* > > *1* > > 0.103 > > 0.159 > > 2.644 > > 22.702 > > 28.424 > > 93.897 > > 201.449 > > > > *2* > > 0.097 > > 0.138 > > 2.641 > > 20.926 > > 32.014 > > 95.195 > > 190.939 > > > > *3* > > 0.123 > > 0.076 > > 3.097 > > 19.88 > > 38.426 > > 90.613 > > 193.376 > > > > *4* > > 0.092 > > 0.098 > > 3.14 > > 23.522 > > 29.509 > > 99.443 > > 192.348 > > > > *5* > > 0.089 > > 0.146 > > 2.938 > > 22.196 > > 34.407 > > 93.898 > > 198.012 > > > > *MIN* > > 0.089 > > 0.076 > > 2.641 > > 19.88 > > 28.424 > > 90.613 > > 190.939 > > 0 > > *MAX* > > 0.123 > > 0.159 > > 3.14 > > 23.522 > > 38.426 > > 99.443 > > 201.449 > > 0 > > *AVG* > > 0.1008 > > 0.1234 > > 2.892 > > 21.8452 > > 32.556 > > 94.6092 > > 195.2248 > > #DIV/0! > > >
