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White stones are popular, frequently mislabeled, and often misunderstood. Learn how to tell if your white stone is a granite, quartzite, or marble. White stones are popular, frequently mislabeled, and often misunderstood.
Engineered quartz and natural quartzite are both popular choices for countertops, backsplashes, bathrooms, and more. Here’s a quick and handy reference for understanding where they come from, what they’re made of, and how they differ.
Quartzite has been gaining in popularity as a countertop material in the past few years. With a look similar to marble and a durability comparable to granite, this natural stone seems to have it all.
Quartzite picks up where sandstone leaves off. It’s a metamorphic rock – one that’s been baked into an extra-tough stone by the heat and pressure that only comes from deep burial way down in Earth’s crust.
Let’s explore some green stones and illuminate their properties, minerals, and geologic origins.
Granite and quartzite have very similar performance statistics. Quartzite is generally harder and denser and the pattern is more like marble which is appealing to many homeowners.
Read about white stones including marble, quartzite, and pegmatite. What colors are available and how does their performance as a countertop differ?
The definitive guide to a commonly mislabeled natural stone, quartzite.
A case study featuring Macaubas Quartzite in a residential kitchen.
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Accessing structured data with SQL is quite different from the full text search of documents on the Web. Structured data in the relational model means data that can be represented in tables -- rows and columns. Each row in a table represents a different object, and the columns represent various 'attributes' of the object. The columns have names and integrity constraints that specify valid values.
Since the column values are named and are represented in a consistent format, you can select rows very precisely, based on their contents. This is especially helpful in dealing with numeric data. You can also join together data from different tables, based on matching column values. You can do useful types of analysis, listing objects that are in one table and missing (or present, or have specific attributes) from a related table. You can extract from a large table precisely those rows of interest, regrouping them and generating simple statistics on them.
This document contains examples of:
INTERACTIVE SQL EXAMPLES
create a table to store information about weather observation stations:-- No duplicate ID fields allowed
CREATE TABLE STATION
(ID INTEGER PRIMARY KEY,
CITY CHAR(20),
STATE CHAR(2),
LAT_N REAL,
LONG_W REAL);
(ID INTEGER PRIMARY KEY,
CITY CHAR(20),
STATE CHAR(2),
LAT_N REAL,
LONG_W REAL);
populate the table STATION with a few rows:
INSERT INTO STATION VALUES (13, 'Phoenix', 'AZ', 33, 112);
INSERT INTO STATION VALUES (44, 'Denver', 'CO', 40, 105);
INSERT INTO STATION VALUES (66, 'Caribou', 'ME', 47, 68);
INSERT INTO STATION VALUES (44, 'Denver', 'CO', 40, 105);
INSERT INTO STATION VALUES (66, 'Caribou', 'ME', 47, 68);
query to look at table STATION in undefined order:
SELECT * FROM STATION; WHERE LAT_N > 39.7;
WHERE LAT_N > 39.7;
ID | MONTH | TEMP_F | RAIN_I |
---|---|---|---|
13 | 1 | 57.4 | .31 |
13 | 7 | 91.7 | 5.15 |
44 | 1 | 27.3 | .18 |
44 | 7 | 74.8 | 2.11 |
66 | 1 | 6.7 | 2.1 |
66 | 7 | 65.8 | 4.52 |
-- matching two tables on a common column is called a 'join'.
-- the column names often match, but this is not required.
-- only the column values are required to match. SELECT * FROM STATION, STATS
WHERE STATION.ID = STATS.ID;
CITY | ST | LAT_N | LONG_W | ID | MONTH | TEMP_F | RAIN_I | |
---|---|---|---|---|---|---|---|---|
13 | Phoenix | AZ | 33 | 112 | 13 | 1 | 57.4 | .31 |
13 | Phoenix | AZ | 33 | 112 | 13 | 7 | 91.7 | 5.15 |
44 | Denver | CO | 40 | 105 | 44 | 1 | 27.3 | .18 |
44 | Denver | CO | 40 | 105 | 44 | 7 | 74.8 | 2.11 |
66 | Caribou | ME | 47 | 68 | 66 | 1 | 6.7 | 2.1 |
66 | Caribou | ME | 47 | 68 | 66 | 7 | 65.8 | 4.52 |
query to look at the table STATS, ordered by month and greatest rainfall, with columns rearranged:
SELECT MONTH, ID, RAIN_I, TEMP_F FROM STATS
ORDER BY MONTH, RAIN_I DESC;
ID | RAIN_I | TEMP_F | |
---|---|---|---|
1 | 66 | 2.1 | 6.7 |
1 | 13 | .31 | 57.4 |
1 | 44 | .18 | 27.3 |
7 | 13 | 5.15 | 91.7 |
7 | 66 | 4.52 | 65.8 |
7 | 44 | 2.11 | 74.8 |
query to look at temperatures for July from table STATS, lowest temperatures first, picking up city name and latitude by joining with table STATION on the ID column:
SELECT LAT_N, CITY, TEMP_F FROM STATS, STATION
WHERE MONTH = 7
AND STATS.ID = STATION.ID
ORDER BY TEMP_F;
CITY | TEMP_F | |
---|---|---|
47 | Caribou | 65.8 |
40 | Denver | 74.8 |
33 | Phoenix | 91.7 |
query to show MAX and MIN temperatures as well as average rainfall for each station:
SELECT MAX(TEMP_F), MIN(TEMP_F), AVG(RAIN_I), ID Quartzcode 1 66 44 Magnum
FROM STATSGROUP BY ID;
MIN(TEMP_F) | AVG(RAIN_I) | ID | |
---|---|---|---|
91.7 | 57.4 | 2.73 | 13 |
74.8 | 27.3 | 1.145 | 44 |
65.8 | 6.7 | 3.31 | 66 |
query (with subquery) to show stations with year-round average temperature above 50 degrees:
Best software for unlocking huawei modems universal flasher. -- rows are selected from the STATION table based on related values in the STATS table.
SELECT * FROM STATION Best software for unlocking huawei modems universal flasher. -- rows are selected from the STATION table based on related values in the STATS table.
WHERE 50 < (SELECT AVG(TEMP_F) FROM STATS
WHERE STATION.ID = STATS.ID);
CITY | ST | LAT_N | LONG_W | |
---|---|---|---|---|
13 | Phoenix | AZ | 33 | 112 |
44 | Denver | CO | 40 | 105 |
create a view (derived table or persistent query) to convert Fahrenheit to Celsius and inches to centimeters:
CREATE VIEW METRIC_STATS (ID, MONTH, TEMP_C, RAIN_C) AS
SELECT ID,
MONTH,
(TEMP_F - 32) * 5 /9,
RAIN_I * 0.3937
FROM STATS;
SELECT ID,
MONTH,
(TEMP_F - 32) * 5 /9,
RAIN_I * 0.3937
FROM STATS;
query to look at table STATS in a metric light (through the new view):
SELECT * FROM METRIC_STATS; MONTH | TEMP_C | RAIN_C | |
---|---|---|---|
13 | 1 | 14.1111111 | .122047 |
13 | 7 | 33.1666667 | 2.027555 |
44 | 1 | -2.6111111 | .070866 |
44 | 7 | 23.7777778 | .830707 |
66 | 1 | -14.055556 | .82677 |
66 | 7 | 18.7777778 | 1.779524 |
another metric query restricted to January below-freezing (0 Celsius) data, sorted on rainfall:
SELECT * FROM METRIC_STATS WHERE TEMP_C < 0 AND MONTH = 1
ORDER BY RAIN_C;
MONTH | TEMP_C | RAIN_C | |
---|---|---|---|
44 | 1 | -2.6111111 | .070866 |
66 | 1 | -14.055556 | .82677 |
Interactive SQL Update Examples
update all rows of table STATS to compensate for faulty rain gauges known to read 0.01 inches low:UPDATE STATS SET RAIN_I = RAIN_I + 0.01;
and take a look:
SELECT * FROM STATS; MONTH | TEMP_F | RAIN_I | |
---|---|---|---|
13 | 1 | 57.4 | .32 |
13 | 7 | 91.7 | 5.16 |
44 | 1 | 27.3 | .19 |
44 | 7 | 74.8 | 2.12 |
66 | 1 | 6.7 | 2.11 |
66 | 7 | 65.8 | 4.53 |
update one row, Denver's July temperature reading, to correct a data entry error:
UPDATE STATS SET TEMP_F = 74.9
WHERE ID = 44
AND MONTH = 7;
WHERE ID = 44
AND MONTH = 7;
and take a look:
SELECT * FROM STATS; MONTH | TEMP_F | RAIN_I | |
---|---|---|---|
13 | 1 | 57.4 | .32 |
13 | 7 | 91.7 | 5.16 |
44 | 1 | 27.3 | .19 |
44 | 7 | 74.9 | 2.12 |
66 | 1 | 6.7 | 2.11 |
66 | 7 | 65.8 | 4.53 |
make the above changes permanent:
-- they were only temporary until now.
-- they were only temporary until now.
COMMIT WORK;
update two rows, Denver's rainfall readings:
UPDATE STATS SET RAIN_I = 4.50
WHERE ID = 44;
WHERE ID = 44;
and take a look:
SELECT * FROM STATS; MONTH | TEMP_F | RAIN_I | |
---|---|---|---|
13 | 1 | 57.4 | .32 |
13 | 7 | 91.7 | 5.16 |
44 | 1 | 27.3 | 4.5 |
44 | 7 | 74.9 | 4.5 |
66 | 1 | 6.7 | 2.11 |
66 | 7 | 65.8 | 4.53 |
Oops! We meant to update just the July reading! Undo that update:
-- undoes only updates since the last COMMIT WORK.
-- undoes only updates since the last COMMIT WORK.
ROLLBACK WORK;
and take a look:
SELECT * FROM STATS; MONTH | TEMP_F | RAIN_I | |
---|---|---|---|
13 | 1 | 57.4 | .32 |
13 | 7 | 91.7 | 5.16 |
44 | 1 | 27.3 | .19 |
44 | 7 | 74.9 | 2.12 |
66 | 1 | 6.7 | 2.11 |
66 | 7 | 65.8 | 4.53 |
Quartzcode 1 66 440
now update Denver's July rainfall reading and make it permanent:
UPDATE STATS SET RAIN_I = 4.50
WHERE ID = 44
AND MONTH = 7;
WHERE ID = 44
AND MONTH = 7;
Quartzcode 1 66 442
COMMIT WORK;
and take a look:
SELECT * FROM STATS; MONTH | TEMP_F | RAIN_I | |
---|---|---|---|
13 | 1 | 57.4 | .32 |
13 | 7 | 91.7 | 5.16 |
44 | 1 | 27.3 | .19 |
44 | 7 | 74.9 | 4.5 |
66 | 1 | 6.7 | 2.11 |
66 | 7 | 65.8 | 4.53 |
delete July data and East Coast data from both tables:
-- note that we use longitude values from the related STATION table to determine which STAT stations were east of 90 degrees.
-- note that we use longitude values from the related STATION table to determine which STAT stations were east of 90 degrees.
DELETE FROM STATS
WHERE MONTH = 7
OR ID IN (SELECT ID FROM STATION
WHERE LONG_W < 90);
WHERE MONTH = 7
OR ID IN (SELECT ID FROM STATION
WHERE LONG_W < 90);
DELETE FROM STATION WHERE LONG_W < 90;
COMMIT WORK;
and take a look:
SELECT * FROM STATION; CITY | ST | LAT_N | LONG_W | |
---|---|---|---|---|
13 | Phoenix | AZ | 33 | 112 |
44 | Denver | CO | 40 | 105 |
MONTH | RAIN_I | ||
---|---|---|---|
13 | 1 | 57.4 | .32 |
44 | 1 | 27.3 | .19 |
View METRIC_STATS, a Fahrenheit-to-Centigrade and inches-to-centimeters conversion of table STATS, reflects the updates made to the underlying table.
SELECT * FROM METRIC_STATS; MONTH | TEMP_C | RAIN_C | |
---|---|---|---|
13 | 1 | 14.1111111 | .125984 |
44 | 1 | -2.6111111 | .074803 |
SQL Constraints
SQL enforces data integrity constraints.Attempt to insert a row for an unknown observation station.
-- The ID value of 33 does not match a station ID value in the STATION table.
-- This is a violation of referential integrity.
INSERT INTO STATS VALUES (33,8,27.4,.19); -- The ID value of 33 does not match a station ID value in the STATION table.
-- This is a violation of referential integrity.
violation of constraint STATS_FOREIGN1 caused operation to fail |
Attempt to update a row with a temperature below the range -80 TO 150.
UPDATE STATS SET TEMP_F = -100 WHERE ID = 44 AND MONTH = 1; violation of constraint STATS_CHECK2 caused operation to fail |
Attempt to insert a row with negative rainfall measurement, outside the range 0 to 100.
INSERT INTO STATS VALUES (44,8,27.4,-.03); violation of constraint STATS_CHECK3 caused operation to fail |
Attempt to insert a row with month 13, outside the range of 1 to 12.
INSERT INTO STATS VALUES (44,13,27.4,.19); violation of constraint STATS_CHECK1 caused operation to fail |
Attempt to insert a row with a temperature above the range -80 TO 150.
INSERT INTO STATS VALUES (44,8,160,.19); violation of constraint STATS_CHECK2 caused operation to fail |
Quartzcode 1 66 44 Mag
Attempt to insert a row with no constraint violations.
INSERT INTO STATS VALUES (44,8,27.4,.10); 1 row inserted |
and take a look:
SELECT * FROM STATS; MONTH | TEMP_F | RAIN_I | |
---|---|---|---|
44 | 8 | 27.4 | .10 |
13 | 1 | 57.4 | .32 |
44 | 1 | 27.3 | .19 |
Attempt to insert a second row of August statistics for station 44.
-- This is a violation of the primary key constraint.
-- Only one row for each station and month combination is allowed.
INSERT INTO STATS VALUES (44,8,160,.19); -- This is a violation of the primary key constraint.
-- Only one row for each station and month combination is allowed.
violation of constraint STATS_PRIMARY_ID_MONTH caused operation to fail |
Embedded SQL C Program Example
Embedded C program to do the following:- Starting with a station name (Denver, in this example), look up the station ID.
- shows single-row select and use of cursor
- note that all C-language variables used in SQL statements are declared in the DECLARE SECTION.
- note that all SQL statements begin with the syntax EXEC SQL and terminate with a semicolon.
Print the station ID.
List all rows for that station ID.
EXEC SQL SELECT ID INTO :station_id
- FROM STATION
WHERE CITY = :city_name;
- {
printf('There is no station for city %sn',city_name);
exit(0);
}
printf('And here is the weather data:n');
EXEC SQL DECLARE XYZ CURSOR FOR
- SELECT MONTH, TEMP_F, RAIN_I
FROM STATS
WHERE ID = :station_id
ORDER BY MONTH;
while (SQLCODE != 100) {
- EXEC SQL FETCH XYZ INTO :mon, :temp, :rain;
if (SQLCODE 100)
- printf('end of listn');
- printf('month = %ld, temperature = %f, rainfall = %fn',mon,temp,rain);
exit(0);
}
for the city denver, station id is 44
and here is the weather data:
month = 1, temperature = 27.299999, rainfall = 0.180000
month = 7, temperature = 74.800003, rainfall = 2.110000
end of list
and here is the weather data:
month = 1, temperature = 27.299999, rainfall = 0.180000
month = 7, temperature = 74.800003, rainfall = 2.110000
end of list