page332
420
Cluster keys
cardinality, 146, 147
cluster depth, 149, 150
clustering ratio, 148
cluster width, 149, 150
definition, 151
logical structure/physical storage,
155, 156
micro-partition, 145–148
objectives, 145
principles, 152
unique indexes, 152–155
Cluster width, 149
Code-templated approach, 227
Common table expression (CTEs), 16, 30
costs, 100
general form, 95
remediating, 101
reusing, 97–100
SELECT statement, 95
use case, 95, 97
Consumption-based model, 5
“Cost-based” optimizers, 15
Create Table AS (CTAS), 48, 131, 168,
384, 385
D
Data catalogs, 351
Data Definition Language (DDL), 7, 326
Data Manipulation Language (DML), 16,
153, 200, 384
Data modeling approach, 357
Data warehouse (DW), 153
dt_lineitem_baseline_sos, 260
Dynamic tables (DTs), 176
E
Entitled data sharing
building engine, 343–345, 347, 348
deploying generation code, 348
designing filter engine, 336
filter engine model, 337
filter engine requirements, 336, 337
Entity relationship diagram (ERD), 395
EXPLAIN keyword, 66
Explicit join notation, 20
F, G, H
Field Programmable Gate
Arrays (FPGAs), 107
Filter engine
client filter, 339, 340
client mask, 340
client object, 326, 339
client specific share, 326
client SQL statements, 342, 343
curated data products, 325
denormalize client
information, 341
engine design, 337
entities, 323
entitlement application, 324
entitlement data model, 324, 325
functional components, 324
source data feeds, 325
SQL statements, 342
Forward declaration error, 21
I
Implicit join notation, 20
INDEX