Explictly set materialized_only=false for test hypertable creations

docs/counter_agg.md

@@ -79,7 +79,7 @@ Now we can make our continuous aggregate:
 
 ```SQL ,ignore
 CREATE MATERIALIZED VIEW foo_15
-WITH (timescaledb.continuous)
+WITH (timescaledb.continuous, timescaledb.materialized_only=false)
 AS SELECT measure_id,
     time_bucket('15 min'::interval, ts) as bucket,
     counter_agg(ts, val, bounds => time_bucket_range('15 min'::interval, ts))

docs/percentile_approximation.md

@@ -200,7 +200,7 @@ Let's do this with our example, we can't use `percentile_disc` anymore as ordere
 
 ```SQL , non-transactional, ignore-output
 CREATE MATERIALIZED VIEW response_times_hourly
-WITH (timescaledb.continuous)
+WITH (timescaledb.continuous, timescaledb.materialized_only=false)
 AS SELECT
     time_bucket('1 h'::interval, ts) as bucket,
     api_id,
@@ -379,7 +379,7 @@ They are often used to create [continuous aggregates]() after which we can use m
 
 ```SQL ,ignore
 CREATE MATERIALIZED VIEW foo_hourly
-WITH (timescaledb.continuous)
+WITH (timescaledb.continuous, timescaledb.materialized_only=false)
 AS SELECT
     time_bucket('1 h'::interval, ts) as bucket,
     percentile_agg(value) as pct_agg

docs/state_agg.md

@@ -749,7 +749,7 @@ VALUES
 
 ```SQL ,non-transactional,ignore-output
 CREATE MATERIALIZED VIEW sa
-WITH (timescaledb.continuous) AS
+WITH (timescaledb.continuous, timescaledb.materialized_only=false) AS
 SELECT time_bucket('1 minute'::interval, ts) AS bucket,
   id,
   state_agg(ts, status) AS agg

docs/tdigest.md

@@ -108,7 +108,7 @@ Next a materialized view with the timescaledb.continuous property is added.  Thi
 including the tdigest in this case, up to date as data is added to the table.
 ```SQL ,non-transactional,ignore-output
 CREATE MATERIALIZED VIEW weekly_sketch
-WITH (timescaledb.continuous)
+WITH (timescaledb.continuous, timescaledb.materialized_only=false)
 AS SELECT
     time_bucket('7 day'::interval, time) as week,
     tdigest(100, value) as digest

docs/test_caggs.md

@@ -17,7 +17,7 @@ SELECT create_hypertable('test', 'time');
 ## Setup continuous aggs
 ```SQL ,non-transactional,ignore-output
 CREATE MATERIALIZED VIEW weekly_aggs
-WITH (timescaledb.continuous)
+WITH (timescaledb.continuous, timescaledb.materialized_only=false)
 AS SELECT
     time_bucket('7 day'::interval, time) as week,
     hyperloglog(64, value1) as hll,

docs/test_candlestick_agg.md

@@ -15,7 +15,7 @@ SELECT create_hypertable('stocks_real_time','time');
 ## Setup Continuous Aggs
 ```SQL,non-transactional,ignore-output
 CREATE MATERIALIZED VIEW cs
-WITH (timescaledb.continuous) AS
+WITH (timescaledb.continuous, timescaledb.materialized_only=false) AS
 SELECT time_bucket('1 minute'::interval, "time") AS ts,
   symbol,
   candlestick_agg("time", price, day_volume) AS candlestick

docs/time_weighted_average.md

@@ -102,7 +102,7 @@ Now we can make our continuous aggregate:
 
 ```SQL ,non-transactional, ignore-output
 CREATE MATERIALIZED VIEW foo_5
-WITH (timescaledb.continuous)
+WITH (timescaledb.continuous, timescaledb.materialized_only=false)
 AS SELECT measure_id,
     time_bucket('5 min'::interval, ts) as bucket,
     time_weight('LOCF', ts, val)

docs/two-step_aggregation.md

@@ -127,7 +127,7 @@ Two-step aggregates expose the internal, re-aggregateable form to the user so th
 
 ```SQL , ignore
 CREATE MATERIALIZED VIEW foo_15
-WITH (timescaledb.continuous)
+WITH (timescaledb.continuous, timescaledb.materialized_only=false)
 AS SELECT id,
     time_bucket('15 min'::interval, ts) as bucket,
     sum(val),

docs/uddsketch.md

@@ -126,7 +126,7 @@ SELECT create_hypertable('test', 'time');
 Now we'll create a continuous aggregate which will group all the points for each week into a UddSketch:
 ```SQL ,non-transactional,ignore-output
 CREATE MATERIALIZED VIEW weekly_sketch
-WITH (timescaledb.continuous)
+WITH (timescaledb.continuous, timescaledb.materialized_only=false)
 AS SELECT
     time_bucket('7 day'::interval, time) as week,
     uddsketch(100, 0.005, value) as sketch